Senior Machine Learning Engineer - Conversion Modeling at unity3d | San Francisco

The Bot CompanyJoin us in creating a revolutionary robot designed to enhance everyday living.Based in San Francisco, our dynamic team consists of talented engineers, designers, and operators hailing from industry leaders like Tesla, Cruise, OpenAI, Google, and Pixar. We've successfully delivered exceptional products and experiences to hundreds of millions of users.Our deliberately streamlined team structure fosters prompt decision-making, eliminating bureaucracy and hierarchy. Each team member is an individual contributor empowered with significant scope, radical ownership, and direct accountability, working collaboratively across the stack in a fast-paced environment focused on rapid iteration and execution.What We Value in CandidatesAt The Bot Company, we seek individuals who exhibit remarkable sharpness and can thrive in high-pressure situations. Throughout the selection process, we expect candidates to showcase:Exceptional mental acuity: You think quickly, absorb information rapidly, and navigate unfamiliar domains with ease.Engineering curiosity: You possess an innate desire to understand system functionalities, extending beyond your primary expertise.High performance mindset: You excel in ambiguous environments and maintain high productivity under challenging conditions.Machine Learning Engineer: World ModelsWe are developing neural simulators capable of comprehending the fundamental

The Bot CompanyAt The Bot Company, we're on a mission to create a friendly robot for every household. Our tight-knit team of visionary engineers, designers, and operators is based in the vibrant city of San Francisco.Our diverse team hails from prestigious organizations like Tesla, Cruise, OpenAI, Google, and Pixar, bringing a wealth of experience from building products that have reached hundreds of millions of users. We know what it takes to craft extraordinary products and user experiences.We maintain a deliberately streamlined team structure to foster quick decision-making and eliminate bureaucratic obstacles. Each team member operates as an individual contributor, wielding significant influence, ownership, and accountability in their work. Our culture encourages rapid iteration and swift execution across the technology stack.

About UsAt Preference Model, we are revolutionizing the future of AI by developing the next generation of training data. While current models demonstrate great power, their effectiveness is limited in diverse applications due to many tasks being out of distribution. We create reinforcement learning environments where models can face real-world research and engineering challenges, allowing them to iterate and learn via realistic feedback loops.Our founding team, hailing from Anthropic's data team, has a rich background in building data infrastructure, tokenizers, and datasets that power Claude. We collaborate with leading AI labs to accelerate AI’s transformative potential and are proudly backed by a16z.About the RoleWe are looking for skilled Machine Learning Engineers to join our efforts in constructing distributed training infrastructure for our reinforcement learning initiatives. Your responsibilities will include:Designing and implementing scalable distributed training infrastructure utilizing PyTorch and Ray.Developing automation tools for monitoring, debugging, and recovery in distributed training environments.Ensuring the reliability, security, and performance of infrastructure to meet the high demands of large-scale machine learning workloads.About YouWe seek individuals with the following qualifications and traits:Required Technical Skills:Experience in building and managing ML infrastructure at scale.Expertise in PyTorch and distributed training paradigms.Hands-on experience with Ray.Familiarity with at least one modern RL training framework such as verl, NeMo-RL, ART, Atropos, or similar.Proficiency in Python and systems programming.Experience with container orchestration tools (Kubernetes), and infrastructure as code methodologies (Terraform).What Makes You Successful:Strong systems thinking with an ability to design for scalability.Exceptional debugging skills across the entire technology stack.A collaborative mindset and strong communication skills to effectively liaise with researchers and engineers.Self-motivated and capable of solving problems independently while taking ownership of projects.

The Bot CompanyAt The Bot Company, we are on a mission to create an innovative robotic assistant for every household.Our dynamic team, composed of talented engineers, designers, and operators, is based in San Francisco. We have a rich background from industry leaders such as Tesla, Cruise, OpenAI, Google, and Pixar, and we have successfully delivered products to hundreds of millions of users, honing our ability to create exceptional products and experiences.We pride ourselves on maintaining a streamlined team structure that fosters swift decision-making and minimizes bureaucracy. Each member is considered an Individual Contributor, granted substantial autonomy, ownership, and accountability. Our culture enables us to work across the technology stack with an emphasis on rapid iteration and execution.What We Seek in CandidatesCandidates for all positions at The Bot Company must exhibit remarkable sharpness and the capacity to thrive in high-pressure environments. We expect candidates to showcase:Exceptional Cognitive Abilities: You possess quick thinking, instant learning capabilities, and the ability to reason across diverse domains.Engineering Curiosity: You demonstrate an innate desire to understand how systems function, even beyond your area of expertise.Performance-Driven Attitude: You excel in fast-paced settings, effectively navigate ambiguity, and thrive under demanding circumstances.Machine Learning: Multimodal Foundation ModelsWe are developing unified foundation models capable of reasoning across text, images, video, and kinematics to inform intelligent robotic behaviors.You will engage with large-scale multimodal networks, overseeing the complete process from data handling to model training and deployment.Your ResponsibilitiesConstruct Native Multimodal Policies: Create architectures where vision, language, and other modalities are represented in a unified manner.Enhance Cross-Modal Reasoning: Explore and implement strategies to ensure that the model not only correlates modalities but also comprehends them (e.g., linking visual physics to kinematic constraints).Manage the Training Loop from Start to Finish: Design, execute, troubleshoot, and refine large-scale training experiments; identify failure points, enhance data mixtures, and tighten evaluations to achieve measurable improvements.Deploy and Refine Real Systems: Integrate models into practical robotic frameworks, enhance robot code for model deployment, and optimize performance for edge inference.

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.

Preference Model creates new types of training data to help artificial intelligence systems improve beyond their current limits. The team specializes in building reinforcement learning environments that test both research and engineering abilities, giving models the chance to learn from realistic feedback. Founded by former members of Anthropic’s data division, Preference Model draws on experience building data infrastructure, tokenizers, and datasets for Claude. The company partners with top AI labs and is backed by a16z. Role overview This entry-level machine learning engineer position is based in San Francisco and is intended for recent graduates. The focus is on building and maintaining the infrastructure that powers Preference Model’s reinforcement learning training pipeline. The team is small, so each engineer takes responsibility for their projects. Deep production experience is not required, but strong technical fundamentals, curiosity about reinforcement learning, and the ability to learn quickly are essential. What you will do Develop and scale distributed training systems with PyTorch Design automation for monitoring, debugging, and recovery during large-scale training runs Collaborate with researchers to turn RL training experiments into dependable infrastructure Enhance performance and reliability for GPU and TPU workloads Requirements Recent graduate (BS, MS, or PhD) in Computer Science, Machine Learning, or a related field Interest in reinforcement learning and AI infrastructure

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.

Join Strava, a leader in the sports technology sector, as a Machine Learning Engineer. In this exciting role, you will apply your expertise in machine learning and data science to develop innovative solutions that enhance the experience of millions of athletes worldwide. Collaborate with cross-functional teams to create algorithms that analyze vast datasets and provide actionable insights to our users.

Join Prima MenteAt Prima Mente, we are pioneers in the field of biology-focused artificial intelligence. Our mission is to generate unique datasets, develop versatile biological foundation models, and translate scientific breakthroughs into real-world clinical applications. Our primary focus is on understanding the brain in-depth, safeguarding it from neurological disorders, and enhancing its function during health. Our dynamic team of AI researchers, experimentalists, clinicians, and operational experts are strategically located in London, San Francisco, and Dubai.Your Role: Foundation Models for BiologyAs a Machine Learning Engineer, you will be instrumental in the design, implementation, and scaling of foundational AI models and infrastructure for multi-omics at an unprecedented scale. Your contributions will facilitate significant advancements in scientific comprehension and lead to groundbreaking applications in the medical and biological fields.Key Responsibilities:Develop high-performance machine learning algorithms optimized for large-scale applications, ensuring utmost reliability and efficiency.Design, implement, and maintain comprehensive experimentation pipelines that allow for rapid iterations, precise assessments, and reproducible research results.Refactor and enhance prototype research code into clean, maintainable, and efficient repositories prepared for production-level deployments.Create fast data processing workflows that can effectively manage extensive datasets to expedite research and model development.Engage in experimental design, with a focus on high-impact experiments that yield the greatest signal-to-noise ratio.Growth ExpectationsIn 1 month, you will initiate initial experiments utilizing state-of-the-art machine learning models, review and apply advanced research papers, and enhance existing code for improved efficiency and precision.By 3 months, you will take ownership of a prototype model architecture, showcasing notable algorithmic enhancements, and contribute to methods for large-scale data ingestion and training.Within 6 months, you will have significantly impacted the implementation of a high-performance foundation model, incorporating key algorithmic optimizations that improve scalability and throughput, along with publishing internal benchmarks that demonstrate substantial effects.

Join Reducto as a Machine Learning EngineerAt Reducto, we empower AI teams to harness real-world enterprise data with unparalleled precision.Much of the enterprise data—ranging from financial documents to healthcare records—remains trapped in unstructured formats such as PDFs and spreadsheets. Our vision models are designed to interpret these documents in a human-like manner, enabling the development of innovative products, training of machine learning models, and automation of processes on a large scale.Our rapid growth is a testament to our success, having achieved a staggering 7x year-over-year revenue increase, collaborating with numerous companies from prominent AI teams like Harvey, Vanta, and Scale to major enterprises including FAANG and leading trading firms.With over $100 million raised from esteemed investors such as A16z, Benchmark, and First Round Capital, we are on the lookout for a talented Machine Learning Engineer to assist in training and deploying models crucial for our core product's success.

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...

Machine Learning EngineerJoin our client, a pioneering company dedicated to developing state-of-the-art non-invasive technology for brain interfacing. They are at the forefront of creating an innovative ultrasound-based platform that not only stimulates but also images brain activity with unmatched precision and depth, paving the way for groundbreaking advancements in neurological treatments and health research.This integrated approach combines cutting-edge hardware, sophisticated real-time software systems, and applied neuroscience to produce scalable solutions that can enhance lives on a global scale.We are looking for a skilled Machine Learning Engineer to play a crucial role in designing and implementing the essential algorithms that will facilitate precise imaging and targeting of brain activity through ultrasound systems.

About the RoleJoin Onyx, an esteemed open-source project that has captivated hundreds of thousands of users. With over 10,000 stars and a vibrant community of over 3,000 members on platforms like Slack and Discord, your contributions could impact millions in the future. Your ImpactAs a Machine Learning Engineer at Onyx, you will play a pivotal role in enhancing our knowledge layer on top of Large Language Models (LLMs). You will tackle complex challenges such as multi-hop question answering, needle-in-haystack retrieval, and advanced Retrieval-Augmented Generation (RAG) techniques. Key ResponsibilitiesDesign and implement knowledge graphs based on LLMs, exploring advanced RAG methods and cutting-edge information retrieval algorithms.Enhance user experience through innovative features like feedback learning, personalized search, and Subject Matter Expert (SME) suggestions.Develop a semantic understanding of organizational priorities to improve Onyx's answering capabilities.Manage projects from initial conception through validation to production deployment.Collaborate closely with our Founders and Head of AI to shape product direction and contribute to our AI/ML strategy. Success Criteria3+ years of experience in AI/ML engineering, focusing on real-world applications.In-depth expertise with PyTorch/TensorFlow, natural language processing (NLP) models, and standard machine learning algorithms.Stay current with advancements in open-source and proprietary LLMs, RAG, and agent frameworks.Strong software engineering skills, capable of building backend features using web frameworks, ORMs, and relational databases.Excellent communication skills, with the ability to collaborate effectively across teams.⭐ Bonus SkillsFamiliarity with full-stack technologies, including TypeScript, React, Next.js, Python, and PostgreSQL.Passion for writing technical blogs to position Onyx as a leader in the field.

About ApiphanyApiphany is an innovative AI company dedicated to advancing physical product development. We empower global leaders in industries such as automotive, aerospace, medtech, and energy to convert vast amounts of unstructured technical data into immediate, actionable insights. Supported by elite investors including Markforged, Databricks, GM, and Character, our mission is to transform engineering decision-making, simplifying complexity for the world's premier manufacturers.Our models are meticulously crafted to address the unique challenges of engineering and manufacturing. They are designed to comprehend principles of physics, design specifications, and program constraints. Our team is a select group of experts from prestigious institutions like Stanford, Berkeley, MIT, UW, and CMU, alongside veterans from GM, Ford, and Genesis Therapeutics. We are committed to redefining hard-tech and constructing a category-defining enterprise together.About the RoleAs a Machine Learning Engineer at Apiphany, you will architect and deploy cutting-edge machine learning models to address some of the most intricate challenges within the physical domain. You will create systems capable of reasoning with complex engineering data, developing AI that grasps physics, design limitations, and real-world performance trade-offs.This role is tailored for innovators eager to expand the horizons of AI applications in the tangible world.

Join Our Team as a Machine Learning Engineer for AssessmentsAt Speak, we're on a mission to transform the language learning experience.Learning a new language has the power to enrich lives, facilitating connections with diverse cultures, career opportunities, and communities. With two billion people worldwide engaged in language studies, the traditional one-on-one tutoring approach remains challenging to scale and has seen little innovation over the years. Speak is revolutionizing this space by offering an AI-powered, human-like tutoring experience that prioritizes conversation. Our platform allows learners to practice speaking, receive instant feedback, and progress through expertly crafted lessons, ensuring a seamless journey from beginner to confident speaker in multiple languages.Since our inception in South Korea in 2019, Speak has rapidly ascended to become the leading language learning app, serving learners across various markets with 15+ languages. Backed by over $150 million in venture funding from prominent investors such as OpenAI, Accel, and Khosla Ventures, our distributed team spans San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.About the RoleWe are seeking a talented Machine Learning Engineer for Assessments to spearhead the development of top-tier assessment systems across our diverse product lines, including Speak for Business and B2C offerings. You will collaborate closely with our Assessment Design Lead, along with teams in Machine Learning, Product, and Engineering, to translate assessment frameworks and rubrics into robust, scalable scoring and feedback systems.This role will encompass the implementation, deployment, and continual enhancement of our assessment algorithms and ML systems. While immediate focus will be on refining and expanding current assessments, the work will also contribute to a foundational capability that can be leveraged across our platform.Your ResponsibilitiesLead the development of assessment ML systems end-to-endDesign, deploy, and maintain scoring models and pipelines (feature extraction, model training, inference, feedback generation).Oversee monitoring, regression tests, and iterative improvements to ensure accuracy standards are met.Establish and implement evaluation frameworksCreate validation and evaluation structures for assessments, incorporating metrics, test sets, and both offline and online analyses.Convert assessment needs into quantifiable acceptance criteria and safeguards.

About MercorMercor operates at the dynamic intersection of labor markets and artificial intelligence research. By collaborating with top-tier AI laboratories and enterprises, we provide the vital human intelligence needed for AI development.Our extensive network of over 30,000 experts trains cutting-edge AI models in a manner akin to educators nurturing students: through the exchange of knowledge, experience, and contextual insights that cannot be encoded. Collectively, our experts generate over $2 million in earnings each day.At Mercor, we're pioneering a new category of work where expertise fuels AI progression. This ambitious endeavor requires a fast-paced, dedicated team. You’ll collaborate with leading researchers, operators, and AI companies at the forefront of systems that are transforming society.As a profitable Series C company valued at $10 billion, we operate in-person five days a week at our state-of-the-art headquarters in San Francisco.

About KreaAt Krea, we are at the forefront of developing cutting-edge AI creative tools that enhance the capabilities of artists and creators. Our commitment is to ensure that these AI technologies are not just accessible but also intuitive, empowering creativity rather than overshadowing it.We envision AI as a transformative medium, facilitating self-expression across diverse formats including text, images, video, sound, and even 3D. Our goal is to innovate smarter, more controllable tools that effectively utilize this medium.The RoleWe are seeking a dedicated Machine Learning Engineer to spearhead large-scale training experiments focused on image and video models.Your Responsibilities:Train foundational diffusion models for advanced image and video generation.Develop and enhance controllability modules such as IPAdapters or ControlNets.Innovate research methodologies and transition them into production.Execute large-scale experiments on high-performance computing clusters, optimizing data pipelines for extensive image datasets.Preferred Experience and Skills:Demonstrated success in working with image or video models at scale, with publications or open-source contributions being advantageous.A robust background in deep learning frameworks and distributed training methodologies.Capacity to rapidly iterate and propose innovative research avenues.More About UsHaving raised over $83 million, we are supported by esteemed Silicon Valley investors, including Andreessen Horowitz and co-founders of the Meta AI Research laboratory, as well as founding members of OpenAI.