Senior Machine Learning Engineer at Databricks | San Francisco

Join the Lightfield TeamAt Lightfield, we are revolutionizing the CRM landscape with our AI-native platform that seamlessly integrates your email, calendar, and meetings. Our innovative solution captures every interaction, transforming it into organized insights—accounts, tasks, follow-ups, and much more—ensuring nothing falls through the cracks.We are committed to reimagining CRM from the ground up. Rather than imposing rigid systems, Lightfield adapts to the actual workflows of companies, automating processes and providing actionable insights that catalyze growth. We are creating the CRM solution we envisioned: fast, intelligent, and genuinely beneficial.Supported by esteemed investors like Greylock, Lightspeed, and Coatue, our team is composed of veterans from Tome, a generative AI presentation tool used by over 25 million people, as well as industry giants like Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.Your RoleAs a pivotal member of Lightfield's AI/ML team, you will spearhead the development of experiences that sit at the heart of our product, crafting applications that truly impress our customers.The current focus is on constructing a robust, domain-specific AI that excels beyond generic large language models (LLMs). We are excited by the challenge of innovating new AI products that empower professionals in their endeavors, and we are eager to expand our AI/ML team to meet this ambition.Key ResponsibilitiesLead the creation of machine learning product development infrastructure, emphasizing scalability and innovation in collaboration and versioning, particularly for LLM training and prompting.Develop and sustain a platform utilized by various teams working on ML products, guaranteeing its scalability, efficiency, and user-friendliness.Work closely with internal teams to integrate ML solutions and establish best practices for software engineering in an AI-focused development environment.Contribute to building a top-tier AI/ML engineering team by recruiting and mentoring new talent.Tackle and resolve complex technological challenges in software engineering at scale, particularly related to AI systems.Who You AreYou possess a Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related field.You have over 6 years of experience in software engineering, with a specialization in ML infrastructure.You demonstrate a robust understanding of deep learning frameworks and cloud services.

About LightfieldLightfield is an innovative, AI-powered CRM that seamlessly integrates with your email, calendar, and meetings. It captures every interaction and transforms it into organized context, including accounts, tasks, follow-ups, and valuable insights, ensuring that nothing is overlooked.We are fundamentally reimagining CRM by focusing on the actual workflows of teams rather than imposing rigid systems. Lightfield learns from real-world usage, automating processes and surfacing insights that drive business growth. We’re creating the CRM platform we’ve always envisioned: fast, intelligent, and genuinely supportive.Supported by notable investors such as Greylock, Lightspeed, and Coatue, our team has a rich background, having previously developed Tome, a generative AI presentation tool utilized by over 25 million users. Many of us have experience with leading companies such as Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleAs a key member of Lightfield's AI/ML team, you will play a vital role in crafting the core experiences of our product, developing cutting-edge applications that delight our customers.Currently, our focus is on building a powerful, domain-specific AI that surpasses generic LLMs.We thrive on the challenge of creating groundbreaking AI products for professionals engaged in serious work, and we are eager to expand our AI/ML team to meet these ambitious goals.What You'll DoDevelop and deliver exceptional, unique AI experiences that sales teams will be excited to use.Collaborate with founders and executives to shape Lightfield's AI/ML strategy.Identify user needs suitable for AI/ML solutions, articulate challenges, and work closely with product leaders to devise solutions.Prototype innovative, LLM-powered experiences and guide their development into reliable product features.Contribute to building a world-class AI/ML engineering team through recruitment and mentorship.Who You ArePossess a BS or MS degree in Computer Science, Artificial Intelligence, or Applied Mathematics.Have over 5 years of experience in developing AI/ML products, particularly in Natural Language Processing (NLP).Demonstrate a solid understanding of deep learning AI/ML frameworks and cloud services.Bring hands-on experience in ML Operations (ML Ops).Bonus PointsExperience leading AI/ML product initiatives...

About LightfieldLightfield is an innovative AI-driven CRM that seamlessly integrates your email, calendar, and meetings into an organized platform. It captures every interaction and transforms it into actionable insights, tasks, accounts, and follow-ups, ensuring that nothing is overlooked.We are revolutionizing the CRM landscape from the ground up. Rather than imposing rigid structures on teams, Lightfield adapts to how businesses naturally operate, automating processes and highlighting insights that foster growth. We are crafting the CRM platform of our dreams: fast, intelligent, and genuinely beneficial.Supported by esteemed investors like Greylock, Lightspeed, and Coatue, our team has a rich history of building impactful products, including Tome, a generative AI presentation tool embraced by over 25 million users. Our collective experience spans companies such as Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleWe are in search of a skilled, innovative, and adaptable engineer excited to take on the challenge of designing, developing, and scaling the foundational infrastructure and systems that power Lightfield's AI-enhanced CRM.At Lightfield, engineers take full ownership of projects from ideation to execution, collaborating across various functions and pushing the boundaries of what is achievable in applied AI and data systems. You will play a pivotal role in crafting and constructing the data models and infrastructure that support a next-generation CRM, ensuring optimal performance, scalability, and resilience.What You'll DoDevelop and sustain full-stack systems, ensuring reliability, scalability, and robust performance.Architect and enhance the data infrastructure and backend services that drive Lightfield's AI-powered CRM.Design and refine data models to facilitate CRM workflows, customer interactions, and AI-derived insights.Create observability and metrics frameworks to promote seamless operations, proactive issue detection, and ongoing enhancements.Guide colleagues, engage in code reviews, and contribute to shaping the engineering culture and best practices.Play a key role in cultivating a top-tier engineering team through recruitment, mentorship, and knowledge exchange.Who You ArePossess 3+ years of software development experience, with a solid foundation in infrastructure, data modeling, and backend systems.Demonstrate extensive experience in designing scalable, high-performance systems.

About LightfieldLightfield is a cutting-edge AI-driven CRM that seamlessly integrates with your email, calendar, and meetings. Our platform captures every interaction, transforming it into organized context—encompassing accounts, tasks, follow-ups, and insights—ensuring no detail is overlooked.We are redefining CRM by focusing on fundamental principles. Rather than imposing rigid systems, Lightfield adapts to the natural workflows of companies, automating processes and revealing insights that propel growth. We're crafting the CRM platform we've always desired: swift, intelligent, and truly beneficial.Our team, backed by prominent investors such as Greylock, Lightspeed, and Coatue, has previously created Tome, a generative AI presentation tool utilized by over 25 million users. Many of us have also contributed to renowned products at Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleWe are seeking a highly motivated and innovative engineer who is passionate about harnessing LLMs to create exceptional product experiences. Join us at the forefront of AI product innovation, where you will develop industry-leading solutions to address critical customer challenges.As an engineer at Lightfield, you will take ownership of projects from conception to execution, collaborating with cross-functional teams throughout the process. You will also help shape our company's product and technical vision, learning from each project as we continue to expand.What You Will DoPartner with product leaders to pinpoint customer challenges, define requirements, and implement LLM-powered solutions.Utilize LLMs as reasoning engines to develop domain-specific AI assistants.Craft and refine prompts, employing techniques such as few-shot learning and chain-of-thought.Design and optimize end-to-end RAG pipelines and agent architectures to effectively utilize both public and proprietary data.Enhance the overall quality of AI agents (e.g. relevance, fidelity, latency) through empirical evaluation and iterative improvements.Create and improve systems and tools that facilitate high-velocity experimentation (e.g. LLM-powered automated evaluation) and personalized product experiences.Stay updated with the latest AI research and integrate cutting-edge techniques into our work.Contribute to defining technical direction and best practices for AI application development at Lightfield.Play a role in building a world-class engineering culture.

Join our dynamic team at Lightfield as a Staff Engineer specializing in Backend Systems. We are looking for a passionate engineer who thrives in a fast-paced environment and is eager to innovate and contribute to the design and implementation of our backend architecture. You will collaborate closely with cross-functional teams to deliver high-quality solutions that enhance our products and services.

About LightfieldLightfield is an innovative AI-driven CRM that seamlessly integrates information from your email, calendar, and meetings. It captures every interaction, transforming it into organized context—managing accounts, tasks, follow-ups, and insights—so that nothing is overlooked.We are redefining CRM from the ground up. Rather than forcing teams into rigid frameworks, Lightfield adapts to the real working styles of companies, automating processes and revealing insights that drive growth. Our vision is to build the CRM platform that we always wanted: fast, intelligent, and genuinely supportive.Supported by prominent investors like Greylock, Lightspeed, and Coatue, our team previously developed Tome, a generative AI presentation tool that has gained over 25 million users. Before Tome, many of us were part of the teams behind Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleLightfield is on the lookout for a proactive Infrastructure Tech Lead to help scale our platform during a period of rapid growth and increasing customer demand. Following our successful exit from private beta, we have witnessed strong adoption from hundreds of businesses joining weekly, including larger teams leveraging our product for mission-critical operations.As we scale our customer base and data volumes surpass initial expectations, our infrastructure is entering a new phase. This role will be pivotal in ensuring that our platform remains fast, reliable, and resilient as Lightfield advances into larger enterprise applications.This is not a position focused on building a team immediately; rather, it offers a high-impact chance for an experienced infrastructure engineer to dive in, tackle core scaling challenges, and help shape the foundational architecture of our system.Your ResponsibilitiesEnhance the reliability and performance of Lightfield's infrastructure as we accelerate customer growth.Lead initiatives to minimize database latency and optimize Postgres performance for high-volume workloads.Elevate operational maturity across the stack, focusing on observability, incident response, and production readiness.Develop scalable systems and infrastructure methodologies to accommodate larger clients and growing usage.Collaborate closely with product and engineering leadership to prioritize critical infrastructure tasks at every growth stage.Contribute to defining the long-term infrastructure roadmap, with the opportunity to influence future team structure and technical direction.

About LightfieldLightfield is an innovative AI-driven CRM that intuitively organizes your communications from email, calendars, and meetings. It captures every interaction, transforming them into structured contexts: accounts, tasks, follow-ups, and insights, ensuring nothing is overlooked.Our mission is to revolutionize CRM by focusing on the natural workflows of teams rather than imposing rigid structures. Lightfield learns from actual business practices, automating processes and surfacing insights that fuel growth. We are developing the CRM platform we've always envisioned: rapid, intelligent, and genuinely supportive.Supported by prestigious investors such as Greylock, Lightspeed, and Coatue, our team boasts a rich history of innovation, having previously created Tome, a generative AI presentation tool embraced by over 25 million users. Many of us have also contributed to major platforms including Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleAt Lightfield, we aim to become the most valuable and impactful company in go-to-market technology. To achieve this, we are recruiting a distinguished go-to-market team to establish our leadership in the CRM space, starting by collaborating with pioneering early-stage companies.We seek a Community Lead who will energize the early-stage founder ecosystem around Lightfield, fostering a vibrant network both online and in-person, centered at our San Francisco headquarters. This role will report directly to our Head of Go-To-Market.What You'll DoBuild and Lead the Lightfield Founder Community. Identify, invite, and nurture relationships with exceptional early-stage founders who are passionate about go-to-market strategies, emphasizing the development of deep, authentic connections.Execute Engaging In-Person Events. Design and implement events that founders genuinely want to join, including gatherings at our San Francisco HQ and activations at third-party trade shows.Create Sustainable Community Programs. Develop structured initiatives such as founder circles, GTM clinics, or “launching your first outbound strategy” cohorts, refining them based on what produces tangible results for participants.Enhance and Manage Our Founder Slack Community. Transform Slack into a thriving peer network where founders exchange go-to-market inquiries, successes, and best practices. Foster discussions, facilitate introductions, and highlight impactful conversations.Transform Conversations into Valuable Content. Capture insights from events and Slack interactions, converting them into engaging content (articles, videos, templates) that illustrate how top founders navigate modern go-to-market strategies.

About LightfieldLightfield is a groundbreaking AI-powered CRM that dynamically organizes your email, calendar, and meeting interactions. By capturing every engagement, it transforms them into actionable insights: accounts, tasks, follow-ups, and critical context, ensuring that nothing is overlooked.We are revolutionizing CRM from the ground up. Rather than constraining teams with inflexible systems, Lightfield evolves through understanding how businesses truly operate, automating processes, and revealing insights that foster growth. We are dedicated to creating the CRM platform of our dreams: quick, smart, and genuinely supportive.Backed by renowned investors including Greylock, Lightspeed, and Coatue, our team has a rich history of innovation, having previously developed Tome, a generative AI presentation tool that serves over 25 million users. Our diverse backgrounds include experience with Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleWe are in search of a talented, imaginative, and adaptable Full Stack Engineer who is excited about the opportunity to create scalable, high-performance features and systems that provide exceptional AI product experiences.At Lightfield, our engineers take on projects from concept to realization, collaborating interdepartmentally to push the boundaries of applied AI systems development. You will partner with a skilled team to deliver industry-leading solutions and help shape the future of Lightfield's product and technical vision.Your ResponsibilitiesWork closely with product leaders to identify customer challenges, define requirements, and execute solutions.Develop and manage full-stack product features and systems from end to end, ensuring reliability, scalability, and performance.Create observability metrics to facilitate seamless operations, proactive issue resolution, and ongoing enhancements.Guide and mentor team members, engage in code reviews, and contribute to cultivating our engineering culture and practices.Play a role in building a world-class engineering team through recruitment, mentorship, and knowledge sharing.Your QualificationsA minimum of 3 years of software development experience, with a solid foundation in both front-end and back-end technologies.Proven experience in building scalable, high-performance systems capable of managing complex customer workflows and extensive data processing.A keen interest in Large Language Models (LLMs) and their applications in real-world scenarios.

About LightfieldAt Lightfield, we are pioneering the future of CRM with our AI-native platform that seamlessly integrates with your email, calendar, and meetings. Our innovative solution captures every interaction, transforming it into structured context, including accounts, tasks, follow-ups, and insights, ensuring that nothing is overlooked.We are fundamentally reimagining CRM by employing a flexible approach that adapts to how teams operate, rather than imposing rigid systems. Lightfield continuously learns, automates processes, and surfaces valuable insights that fuel growth. We are dedicated to creating a CRM platform that is not only fast and intelligent but also genuinely helpful.Our team is backed by prestigious investors like Greylock, Lightspeed, and Coatue, and has a rich history in building successful products, including Tome, a generative AI presentation tool utilized by over 25 million users. Our collective experience spans notable companies such as Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleJoin our dynamic AI/ML team at Lightfield, where we are developing the core experiences of our product through cutting-edge applications that amaze our customers. We are currently focused on creating a robust, domain-specific AI that surpasses conventional LLMs.We thrive on the challenge of crafting innovative AI solutions for professionals engaged in significant work, and we're eager to expand our AI/ML team to rise to this challenge.Your ResponsibilitiesDesign and deliver extraordinary AI experiences that empower sales teams.Collaborate closely with founders and executives to shape Lightfield's AI/ML strategy.Lead the training of new models utilizing both historical and synthetic training data.Develop and prototype innovative LLM-driven experiences, transforming them into robust product features.Contribute to building a top-tier AI/ML engineering team through recruitment and mentorship.Your Profile5+ years of industry experience in Natural Language Processing (NLP) with a strong portfolio of model training.Solid understanding of deep learning AI/ML frameworks and cloud services.Hands-on experience in ML Operations (ML Ops).Deep expertise in NLP and model training, particularly with Large Language Models (LLMs).Demonstrated ability to adapt open-source generative models for specific applications, with a comprehensive understanding of their architecture.

About LightfieldLightfield is a revolutionary AI-native CRM that seamlessly integrates with your email, calendar, and meetings. It meticulously captures every interaction, transforming it into well-organized context, including accounts, tasks, follow-ups, and insights, ensuring that no detail is overlooked.We are redefining the CRM landscape from the ground up. Rather than compelling teams to adhere to inflexible systems, Lightfield intelligently adapts to how companies operate, automating processes and surfacing insights that foster growth. We are crafting the CRM platform we've always envisioned: fast, intelligent, and genuinely beneficial.Supported by esteemed investors such as Greylock, Lightspeed, and Coatue, our team previously developed Tome, a generative AI presentation tool utilized by over 25 million people. Before Tome, many of us contributed to the success of Llama, Instagram, Facebook Messenger, Pinterest, Google, and Salesforce.About the RoleWe have successfully launched a product that founders adore, with nearly 2,000 companies registering since our debut in November. We are now poised to establish our first direct sales strategy. With strong product-led growth in self-service, we need an individual who can transform that momentum into significant $20K+ contracts with Series A/B startups.This position is foundational. You will not inherit an established playbook or team, but you will be presented with genuine demand. We have a growing number of multi-seat accounts, engaged teams, and high-intent signals ready to be harnessed. The pipeline is established; we require someone capable of converting it. You will leverage our product-led growth data to identify high-potential accounts, complementing it with targeted outreach to VC-backed startups, managing the complete sales cycle from initial meetings through to closing.You will report directly to the Head of GTM. Initially, you will oversee the entire sales process—crafting discussion points, developing pilot frameworks, and finalizing deals. As we scale into larger markets, you will play a key role in shaping the future of our sales organization.What You'll DoManage the complete sales cycle. Conduct discovery, demonstrations, pilot programs, and close deals ranging from $20K to $50K with 30-day cycles. Your clients will include VP Sales, RevOps leaders, and technical founder-CEOs at startups with 20–250 employees.Enhance our existing pipeline and build upon it. We have numerous active accounts with team adoption, multi-seat usage, and indications of CRM migration. You will enrich and prioritize this existing base while layering targeted outreach to Series A/B portfolios to achieve 3–4x pipeline coverage.Develop the sales playbook. Create pilot templates, mutual action plans, and collateral that will serve as the foundation for the team that follows.

tvScientific seeks a Machine Learning Platform Engineer to help shape the company’s advertising technology. This position can be based in San Francisco, CA, or performed remotely from anywhere in the United States. Role overview This role focuses on building and refining machine learning models that drive the core of tvScientific’s advertising platform. The work combines technical skill with creative problem-solving to support the platform’s effectiveness. What you will do Develop and optimize machine learning models to enhance advertising performance Collaborate with team members to deliver solutions that balance innovation, scalability, and reliability Apply technical expertise to address challenges at the intersection of technology and creative thinking Location Candidates may work from San Francisco, CA, or remotely within the US.

The Applied AI team at Databricks is at the forefront of pioneering GenAI-powered products. In recent years, we have successfully launched the Databricks Assistant, AI/BI Genie, and Agent Bricks, collaborating with product teams to significantly enhance LLM quality for these offerings. These innovations are utilized by hundreds of thousands of Databricks users daily. We are dedicated to solving complex challenges such as code suggestion, error detection and correction, text-to-SQL generation, automatic pipeline generation, and knowledge QA.As we continue to evolve our GenAI products, we are looking for multiple GenAI Engineers at various experience levels to lead the next phase of our development. Our goals for 2025 include improving LLM quality, broadening GenAI capabilities across Databricks products, and reinforcing our platform architecture to facilitate seamless AI interactions on a large scale.

About This Role Join Databricks as a Software Engineer focused on GenAI inference, where you will play a pivotal role in designing, developing, and enhancing the inference engine that drives our Foundation Model API. Collaborating at the intersection of research and production, you will ensure our large language model (LLM) serving systems are optimized for speed, scalability, and efficiency. Your contributions will span the entire GenAI inference stack, from kernels and runtimes to orchestration and memory management. What You Will Do Participate in the design and implementation of the inference engine, collaborating on a model-serving stack tailored for large-scale LLM inference. Work closely with researchers to integrate new model architectures or features such as sparsity, activation compression, and mixture-of-experts into the engine. Optimize latency, throughput, memory efficiency, and hardware utilization across GPUs and other accelerators. Build and maintain tools for instrumentation, profiling, and tracing to identify bottlenecks and inform optimization efforts. Develop scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads. Ensure reliability, reproducibility, and fault tolerance in inference pipelines, including A/B launches, rollback, and model versioning. Integrate with federated and distributed inference infrastructure, orchestrating across nodes, balancing load, and managing communication overhead. Engage in cross-functional collaboration with platform engineers, cloud infrastructure, and security/compliance teams. Document and share insights, contributing to internal best practices and open-source initiatives as appropriate.

Join us in creating the backbone of data infrastructure for real-world robotic operations.As robotics transitions from research labs to real-world applications across factories, warehouses, vehicles, and field deployments, understanding the intricacies of robotic performance becomes critical. When robots encounter failures or unexpected behaviors, data analysis is key to deciphering the underlying issues.At Foxglove, we are at the forefront of building tools for observability, visualization, and data infrastructure that empower robotics and autonomous systems teams to manage, analyze, and derive insights from vast amounts of multimodal sensor data collected from operational systems and production fleets.Role OverviewWe are seeking a passionate ML Platform Engineer with robust infrastructure expertise to design, deploy, and scale our data platform systems. This platform-centric role will allow you to take charge of the infrastructure layer that facilitates machine learning in production environments, going beyond just the models themselves.Your responsibilities will encompass ensuring the reliability, scalability, and performance of the ML platform, including areas such as inference serving, pipeline orchestration, training infrastructure, and evaluation frameworks. You will be tackling substantial challenges such as managing petabyte-scale multimodal robotics data and optimizing high-throughput retrieval and embedding pipelines in a hands-on infrastructure capacity.Key ResponsibilitiesDesign and operationalize production inference infrastructure, focusing on model serving, autoscaling, load balancing, and cost efficiency across cloud environments.Own the platform architecture for embedding and retrieval pipelines that enable semantic search across multimodal robotics data (image, video, point cloud, and time series).Develop and sustain the training and evaluation infrastructure that supports rapid model performance iteration, including job orchestration, experiment tracking, and dataset versioning.Lead decisions on cloud infrastructure (AWS/GCP) that affect latency, throughput, reliability, and scalability.Establish platform abstractions and internal tools that empower product engineers to deliver ML-enhanced features without managing infrastructure directly.Assess, integrate, and operationalize third-party ML infrastructure components while establishing clear build vs. buy frameworks for the team.

tvScientific, powered by Pinterest, develops a connected TV (CTV) advertising platform designed for performance marketers. The platform combines media buying, optimization, measurement, and attribution to automate and improve TV advertising. Built by professionals in programmatic advertising, digital media, and ad verification, tvScientific aims to deliver measurable results for advertisers. Role overview As a Machine Learning Platform Engineer, you will join a team that operates where Site Reliability Engineering meets low-latency distributed systems. This team advances Pinterest’s real-time machine learning and measurement infrastructure, focusing on sub-millisecond decision-making and high-throughput data access. Seamless integration with Pinterest’s core stack is central to the work. What you will do Design and build systems to keep queries and RPCs fast and reliable, even during periods of heavy demand. Develop and enhance the foundation of the machine learning training and serving stack. Address challenges in storage, indexing, streaming, fan-out, and managing backpressure and failures across services and regions. Collaborate with software engineering, data infrastructure, and SRE teams to ensure systems are observable, debuggable, and ready for production. Key areas of focus I/O scheduling and batching Lock-free or low-contention data structures Connection pooling and query planning Kernel and network tuning On-disk layout and indexing strategies Circuit-breaking and autoscaling Incident response and failure management NixOS Defining and maintaining SLIs and SLOs This position is a strong fit for engineers interested in building and operating large-scale infrastructure, particularly those who enjoy working on real-time systems, observability, and reliability.

About Taskrabbit:Taskrabbit is an innovative marketplace platform that seamlessly connects individuals with Taskers to manage everyday home tasks, including furniture assembly, handyman services, moving assistance, and much more.At Taskrabbit, we aim to transform lives one task at a time. We celebrate innovation, inclusion, and hard work, fostering a collaborative, pragmatic, and fast-paced culture. We seek talented, entrepreneurially minded, data-driven individuals who possess a passion for empowering others to pursue their passions. In partnership with IKEA, we are creating more opportunities for individuals to earn a consistent, meaningful income on their terms by establishing enduring relationships with clients in communities globally.Taskrabbit operates as a hybrid company, with team members located across the US and EU, and has been recognized as a Built In — Best Places to Work for 2022, 2023, and 2024, receiving accolades across various national and regional categories. Join us at Taskrabbit, where your contributions will be significant, your ideas appreciated, and your potential maximized!This position operates on a hybrid schedule, requiring two days of in-office collaboration per week. It can be based in our San Francisco office or our new New York City office (opening March 2026).About the RoleMachine Learning is a foundational element at Taskrabbit, and we are in search of an experienced Senior Machine Learning Engineer to join our team and help mold the future of ML/AI at Taskrabbit. This distinct, full-stack role is designed for someone who is enthusiastic about the entire machine learning lifecycle—from initial research and model development to constructing the robust infrastructure necessary for deploying and scaling your innovations.As a Senior Machine Learning Engineer, you will engage with exciting challenges that directly influence how users discover and interact with home services on the Taskrabbit platform. You will play a vital role in enhancing our capabilities in areas such as search ranking, content discovery, and recommendation systems. Collaborating closely with data scientists and fellow engineers, you will design and implement cutting-edge algorithms, ensuring the scalability, reliability, and optimization of our models in production alongside software engineers.

About VSCO At VSCO, we empower photographers with an innovative platform that provides essential tools, a vibrant community, and the visibility needed for creative and professional growth. We cultivate an authentic creative environment that welcomes photographers of all skill levels, offering a space that inspires opportunity, collaboration, and connection. Our mission is to support photographers in their journeys, enabling them to thrive and connect with fellow creatives and businesses through our comprehensive suite of tools, available on both mobile and desktop. We seek individuals who are passionate and proactive in advancing our mission. Our team members have the opportunity to make a significant impact, and we believe that collaborative efforts yield stronger results. Our core values are essential to our team culture and guide our hiring process. Learn more about what you can expect when joining VSCO on our Careers Page. About The Role As a Senior Machine Learning Engineer, you will harness the power of AI and machine learning to create innovative, reliable user-facing product features. You will leverage your extensive technical background and hands-on experience in deploying machine learning models to deliver impactful solutions based on real-world feedback. Your focus on measurable outcomes and customer satisfaction drives your work, blending innovation with practical implementation. You will be highly skilled in Python and adept across the data and machine learning stack, enabling you to develop and launch models efficiently while ensuring scalability and maintainability. Whether working with traditional algorithms or cutting-edge deep learning and generative AI, you will expertly navigate the complexity of each problem, managing every phase from defining the challenge to deployment and iterative improvement. Your dedication to software engineering excellence will inform your thoughtful approach to system design for machine learning, encompassing data quality, pipeline design, feature workflows, model serving, and ongoing monitoring and enhancement. By integrating machine learning deeply within our cohesive product experiences, you will collaborate effectively with cross-functional teams, aligning on objectives, defining success metrics, and driving meaningful outcomes. You will stay informed about the rapidly evolving AI landscape, maintaining a discerning perspective that allows your team to focus on significant advancements while avoiding distractions. The Day to Day Design and implement ML-powered features for search, discovery, personalization, and more.

Job OverviewJoin Eragon as a Machine Learning Engineer and lead the charge in transforming innovative AI models into scalable, production-grade systems. This position is pivotal in bridging research and real-world applications by designing and optimizing systems that enhance vital workflows throughout the enterprise.In collaboration with our research, product, and engineering teams, you will convert cutting-edge capabilities into dependable, high-performance systems ready for production.Key ResponsibilitiesModel Development & Deployment: Craft, refine, and deploy machine learning models within production settings.Systems Engineering: Architect scalable pipelines for training, inference, evaluation, and comprehensive monitoring.Performance Optimization: Enhance the latency, throughput, cost-efficiency, and reliability of ML systems.Data & Infrastructure: Manipulate large datasets and ensure seamless integration of models with internal systems and APIs.Cross-Functional Collaboration: Collaborate with product and engineering teams to provide end-to-end AI functionalities.Evaluation & Monitoring: Develop robust evaluation frameworks and feedback loops to ensure system effectiveness.

At Sciforium, we are pioneering the future of AI infrastructure by creating cutting-edge multimodal AI models and a proprietary, high-efficiency serving platform. With substantial financial backing and direct support from AMD engineers, our team is rapidly expanding as we develop the comprehensive stack that drives advanced AI models and real-time applications.About the RoleIn the capacity of a Machine Learning Engineer, you will engage with the entire foundation-model stack, encompassing pretraining and scaling, post-training and Reinforcement Learning, sandbox environments for evaluation and agentic learning, and deployment + inference optimization. You’ll have the opportunity to rapidly iterate on research ideas, contribute to production-grade infrastructure, and help deliver models capable of addressing real-world challenges at scale.Your ResponsibilitiesThis position offers diverse tracks - candidates can specialize or contribute across multiple areas. Key responsibilities include:Pretraining & ScalingTrain expansive byte-native foundation models utilizing vast, heterogeneous data sources.Formulate stable training methodologies and scaling laws tailored for innovative architectures.Enhance throughput, memory efficiency, and resource utilization across extensive GPU clusters.Establish and maintain distributed training infrastructures alongside fault-tolerant pipelines.Post-training & Reinforcement LearningBuild out post-training frameworks (SFT, preference optimization, RLHF/RLAIF, RL).Curate and produce specialized datasets aimed at enhancing specific model capabilities.Develop reward models and evaluation systems to facilitate ongoing improvements.Investigate inference-time learning and computational strategies to boost performance.Sandbox Environments & EvaluationCreate scalable sandbox environments for agent assessment and learning.Generate realistic, high-signal automated evaluations for reasoning, tool usage, and safety.Design both offline and online environments that support RL-style training at scale.Implement instrumentation for observability, reproducibility, and rapid iteration.Deployment & Inference OptimizationOptimize deployment strategies to ensure models are efficient and effective in real-world applications.