Senior Data Engineer at tvScientific | San Francisco, CA

Join tvScientific as a Machine Learning Engineer where you will leverage cutting-edge machine learning techniques to enhance our advertising platform. You will be responsible for developing and optimizing algorithms that drive effective ad targeting and analytics. Collaborate with cross-functional teams to integrate machine learning solutions that improve user engagement and maximize return on investment for our clients.

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.

Join tvScientific as a Senior Machine Learning Engineer and be at the forefront of developing and deploying innovative machine learning solutions that drive advertising efficiency. Your expertise will contribute to building cutting-edge algorithms and systems that enhance our clients' marketing strategies.In this role, you will collaborate with cross-functional teams to translate business requirements into technical specifications, and develop scalable models that leverage large datasets. Your passion for machine learning and data science will help shape the future of advertising technology.

Join tvScientific as a Senior Machine Learning Operations Engineer and play a pivotal role in deploying and managing ML models at scale. You will work closely with data scientists and software engineers to optimize and streamline ML workflows, ensuring the delivery of high-quality products to our clients. This position offers the flexibility to work remotely from anywhere in the United States.

Join tvScientific as a Sales Engineer where you will play a critical role in bridging the gap between our innovative technology and our sales strategy. You will work closely with our sales team to create tailored solutions that meet our clients' needs, leveraging your technical expertise to ensure successful implementation and customer satisfaction.

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.

At Lyft, we are driven by our mission to connect and serve our communities. We strive to foster a workplace where every team member feels valued and has the opportunity to excel. With over half a billion rides and counting, Lyft is tackling complex challenges on a grand scale, utilizing cutting-edge AI and Machine Learning technologies to enhance customer experiences. The Artificial Intelligence, Machine Learning, and Operations Research Platforms team (AIMLOR) is on the lookout for a Senior Machine Learning Engineer who will play a pivotal role in constructing AI Platform components that empower essential AI applications across Lyft. Mastery in Generative AI and platform development is crucial for this position. You will contribute to our platform that facilitates real-time, online, and offline AI and ML model execution, development, and iteration. Collaborating with a team of talented Machine Learning and Software Engineers, you will work on intricate problems and define solutions that make a direct impact on our systems throughout the organization. If you are enthusiastic about building an AI Platform at scale with applications spanning every aspect of our company, we want to hear from you. If you are a creative thinker with a strong background in AI and machine learning systems and are passionate about leveraging data to solve business challenges in a dynamic, innovative, and collaborative environment, we invite you to apply.

About Pinterest Pinterest helps millions of people worldwide discover new ideas, try fresh possibilities, and collect inspiration for their lives. The company’s mission is to empower individuals to curate a life they love, starting with a talented and diverse team. Pinterest values innovation and encourages employees to fuel growth for millions. Team members are supported in turning passion into opportunity, and the company celebrates different backgrounds while offering flexibility to help everyone do their best work. AI plays a central role at Pinterest, serving as a partner to boost creativity and impact. The hiring process focuses on both foundational skills and how candidates collaborate with AI. For more on Pinterest’s approach to AI in hiring, see this overview. About tvScientific tvScientific is a leading CTV advertising platform built for performance marketers. The platform uses large-scale data and advanced technology to automate and optimize TV advertising, helping businesses achieve measurable results. Media buying, optimization, measurement, and attribution all work together in a single solution. The team behind tvScientific includes experts in programmatic advertising, digital media, and ad verification, building tools for advertisers focused on business growth. Role Overview: Staff Data Engineer The Staff Data Engineer will lead the design, implementation, and improvement of identity services and the data governance platform at tvScientific. This role is critical for maintaining data integrity, privacy, and governance across the company. The position involves working at the intersection of data engineering, identity resolution, privacy, and platform reliability. As an individual contributor, the Staff Data Engineer will help define and carry out the strategic vision for data engineering within the organization. Location San Francisco, CA, US or Remote, US

About tvScientifictvScientific stands as the pioneering CTV advertising platform meticulously designed for performance marketers. By harnessing extensive datasets and advanced scientific methodologies, we automate and refine TV advertising to achieve measurable business results. Our comprehensive solution integrates media buying, optimization, measurement, and attribution into a streamlined platform. Developed by industry veterans with a robust background in programmatic advertising, digital media, and ad verification, our platform offers a reliable CTV performance solution that empowers advertisers to elevate their business.As a Senior Machine Learning Engineer at tvScientific, you will be instrumental in building the machine learning and AI systems that underpin our Connected TV ad-buying platform, focusing on real-time bidding, campaign optimization, and incremental measurement at scale. As an adtech innovator, we are tackling the complex challenge of making CTV advertising quantifiable. Our platform enables advertisers to purchase ads across a diverse CTV ecosystem—including Hulu, Pluto TV, Disney+, HBO Max, and numerous FAST channels—while demonstrating that these ads generate tangible business results.

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 Mariana MineralsMariana Minerals is a pioneering software-driven, vertically integrated minerals company dedicated to supplying the essential minerals that fuel modern energy, artificial intelligence, and defense technologies. We are transforming the minerals supply chain by leveraging extensive industry knowledge alongside cutting-edge software, automation, and data-centric decision-making.The RoleAs we build the critical minerals supply chain from the ground up, we seek a highly skilled Senior Machine Learning Engineer to help drive our autonomous operations.Unlike traditional software companies, we are a mining company that develops our own software solutions. Mariana designs, builds, commissions, and operates our own mines and refineries, where we create proprietary chemical processes. Currently, we are producing battery-grade lithium salts from real oil and gas wastewater at our facilities. Our first commercial-scale lithium production facility, Lithium One, is set to commence initial production in the first half of 2027.In your role as a Senior Machine Learning Engineer, you will spearhead the design and implementation of machine learning systems that directly optimize the operations of our mineral refining facilities and guide significant investment and operational decisions. Your contributions will be visible in tangible metrics such as recovery rates, energy consumption, reagent usage, and equipment uptime.The TechThis position involves some of the most compelling applied AI work available today.Our internal platform, PlantOS, utilizes the same reinforcement learning frameworks that power self-driving cars and humanoid robots, adapted for the autonomous and short-interval control of mineral refining circuits. Our models dynamically adjust operating parameters in real time, optimizing for lithium recovery, reagent consumption, energy efficiency, and equipment uptime simultaneously.The working environment is complex and ever-changing; variations in wastewater compositions, ore grades, and aging equipment require the system to adapt continuously. The ultimate objective is to achieve fully autonomous refining operations—when you implement your solutions here, you will witness the physics of the process evolve.What You’ll DoCollaborate closely with Mariana’s process chemistry and engineering teams to develop innovative, data-driven models of core chemical unit operations.Train and deploy reinforcement learning models to optimize operational processes.

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.

Join Our Mission to Empower Communities! At GoFundMe, we are the leading global platform dedicated to helping people support each other. Since our inception in 2010, we've facilitated over $40 billion in fundraising, uniting individuals and nonprofits in a safe and engaging environment. We are seeking a passionate and experienced Senior Manager, Machine Learning Engineering to join our Applied Science team. In this pivotal role, you will spearhead a dynamic team tasked with creating impactful machine learning solutions that enhance user experiences and drive business growth. Your responsibilities will include designing, developing, and deploying cutting-edge services and applications utilizing advanced machine learning and AI methodologies, such as generative AI, personalized recommendations, search systems, and classification techniques. This position requires exemplary leadership capabilities to ensure both strategic vision and tactical execution, backed by your extensive knowledge of machine learning, AI, and secure software practices. This role is based in the vibrant San Francisco Bay Area, with an expectation of being in the office three times a week.

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.

The Applied AI team at Databricks is dedicated to pioneering advancements in GenAI-driven products. In recent years, we have successfully launched notable innovations such as the Databricks Assistant, AI/BI Genie, and Agent Bricks. These products are utilized by hundreds of thousands of Databricks users daily. We are addressing complex challenges such as code suggestions, error detection and correction, text-to-SQL generation, automatic pipeline creation, and knowledge QA. As our GenAI products continue to advance, we are on the lookout for multiple GenAI Engineers, ranging from junior to senior levels, to spearhead the next phase of development. In 2025, our focus will be on enhancing the quality of LLMs, broadening GenAI functionalities across Databricks products, and fortifying our platform architecture to facilitate seamless AI interactions at scale.

Join Our Innovative Team at KiddomAt Kiddom, we are revolutionizing education through our cutting-edge platform that champions student equity and growth. We seamlessly integrate high-quality instructional materials with engaging digital learning experiences. Our robust curriculum management tools empower schools and districts to effectively manage their curriculum, leading to personalized learning experiences that cater to the unique needs and aspirations of local communities. Our high-quality curriculum is enriched with insightful data analytics for teachers and leaders, fostering continuous improvement in instructional strategies, school programming, and professional development.Your Role and ResponsibilitiesAs a vital member of Kiddom’s AI team, you will play a critical role in developing the backbone of our search, recommendation, and insights systems. Your contributions will directly enhance the experience of teachers and students by providing timely insights, personalized content, and intelligent assistance tailored to their needs.

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.