Applied Machine Learning Engineer at fal | San Francisco

We are seeking a talented Applied Machine Learning Engineer with a comprehensive understanding of the generative media landscape. You should possess an up-to-date knowledge of emerging methodologies and be capable of identifying gaps in the current market. Your role will involve innovating and developing machine learning models that enhance user experiences, requiring both novel training techniques and the fine-tuning of existing models with fresh datasets.

At fal, we are revolutionizing generative-media infrastructure, empowering users to transform raw creativity into polished experiences within minutes. As we experience rapid growth, we are seeking a Growth Engineer who can seamlessly merge agile engineering skills with a product-oriented growth mindset—someone capable of delivering code in the morning and forging partnerships over coffee in the afternoon. Why This Role is Crucial This position places you at the crossroads of engineering, product development, and go-to-market strategies. Your innovative prototypes, experiments, and engaging content will serve as the initial interaction for creators, studios, and Fortune 500 innovation teams. A successful execution of your role will be reflected in the company's performance metrics and dashboards. Your Responsibilities Quickly develop lightweight client libraries, demo applications, or event microsites. Conduct data-driven experiments by segmenting cohorts, designing A/B tests, and automating reporting. We maintain a clear, metric-focused view of acquisition costs and activation rates for every segment. Create compelling blog posts, tweets, and teardown threads devoid of “AI slop.” Your content will consistently attract qualified sign-ups and ignite industry discussions. Manage customer interactions: Engage with prospects, troubleshoot their initial calls, and represent fal at meetups and hackathons, leaving prospects impressed with your understanding and speed of execution. Identify high-impact challenges, implement time-boxed solutions, and deliver results. After onboarding, you will propose your own roadmap, and we are inclined to support your initiatives. You May Be a Great Fit If You... Can code at lightning speed. You are fluent in Python and JavaScript (Next.js, React) and can integrate APIs, CLIs, and scrapers before lunch. Thrive on metrics. You utilize SQL, Amplitude/Looker, or plain-text CSVs to derive insights swiftly. Possess persuasive writing skills. Your copy is engaging, helpful, and opinionated, driving clicks. Enjoy interacting with people as much as coding. You are energized by demos, direct messages, and in-person events. Seek ownership. You find excitement in tackling ambiguous problems and starting from a blank slate. Are passionate about generative media. You keep up with the latest diffusion papers for fun and have strong opinions on video model architectures. Preferred Qualifications Prior experience in product-led growth (PLG) or developer-tool startups. Familiarity with growth analytics stacks.

fal is at the forefront of developing the most rapid and scalable infrastructure for AI inference. Our fal Serverless platform powers over 1,300 endpoints on the fal Marketplace, efficiently managing tens of millions of requests daily across various production workloads. Enterprises leverage fal Serverless to seamlessly deploy, operate, and scale custom AI models without the burden of infrastructure management. Our platform excels in autoscaling, observability, and operational efficiency, all handled through fal’s intuitive UI. Initially designed as internal infrastructure to support fal’s own scale, Serverless was publicly launched for enterprise clients in early 2025 and has since evolved into a core revenue-generating product experiencing rapid adoption. As one of the fastest-growing AI startups, fal has reached Series D funding with a valuation of $4.5 billion, all while maintaining a lean team of approximately 70 employees. Joining us means becoming an early member of a dynamic team where your contributions directly influence a foundational product.

Founded in 2009 in the heart of Silicon Valley by visionaries Marc Andreessen and Ben Horowitz, Andreessen Horowitz (commonly known as a16z) is a premier venture capital firm dedicated to supporting innovative entrepreneurs who are shaping the future through technology. We pride ourselves on being stage agnostic, investing in technology companies from seed to venture and growth stages across diverse sectors including AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and initiatives contributing to American dynamism. Currently managing $90B across multiple funds, a16z is at the forefront of technological innovation.Our team is characterized by a profound respect for entrepreneurs and the intricate process of building companies; we understand the founder's journey firsthand. Our portfolio boasts industry leaders such as Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. We are committed to empowering founders and their teams to make a significant impact on the world.

Join fal as an experienced Enterprise Product Manager, where you will spearhead our enterprise product initiatives. Collaborate closely with large-scale clients to understand their unique needs, influence pricing strategies, and define essential features tailored for organizational use cases.

fal is seeking a Business Development Representative (BDR) based in San Francisco. This role centers on generating new business, building relationships with clients, and collaborating with both sales and marketing teams to help drive growth. Key responsibilities Find and pursue new business opportunities in the San Francisco area Develop and maintain strong connections with clients Partner with sales and marketing colleagues to achieve growth goals What fal values Drive to succeed in sales and business development Clear communication and the ability to build client rapport Interest in supporting fal's market expansion

Join Perplexity as an Applied Machine Learning Engineer and be at the forefront of innovation in artificial intelligence. You will design, develop, and refine advanced AI models that enhance user experiences globally. Your expertise in machine learning will allow you to create scalable solutions for user personalization, query comprehension, and content discovery, catering to the curiosity of millions.Key ResponsibilitiesUtilize cutting-edge ML and LLM techniques to address challenges in:Personalization (LLM memory, context summarization, retrieval, and ranking);Query Understanding (intent modeling, rewriting, agentic decomposition);Content Discovery (feed ranking and surfacing).Conduct thorough evaluations of LLM/ML models through offline and online methods, designing comprehensive experiments and metrics that yield insights into quality and impact.Manage the full model lifecycle from research to deployment, including data analysis, modeling, evaluation, A/B testing, and iterative enhancements.Collaborate with cross-functional teams, including engineers, PMs, data scientists, and designers, to ensure AI implementations yield significant product enhancements.Stay updated on ML/AI advancements by assessing and integrating new research and algorithms into the product lifecycle.Preferred QualificationsOver 5 years of experience in developing and deploying robust ML/AI models for large-scale, user-centric or data-driven applications.Extensive knowledge in deep learning frameworks (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and ranking.Proficient software engineering skills (Python, production-level codebases, collaborative development).Comprehensive experience across the entire ML lifecycle: data analysis, feature engineering, model development, evaluation, and ongoing monitoring/improvement.Effective collaborator and communicator; thrives in fast-paced, cross-functional environments.Inquisitive, motivated by user/product impact, and passionate about advancing applied ML and AI.Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field (or equivalent experience).

About UsAt Applied Compute, we specialize in creating Specific Intelligence solutions for enterprises, developing agents that learn continuously from an organization’s processes, data, expertise, and objectives. We recognize a significant gap between the capabilities of AI models in isolation and their practical applications in real-world business contexts. Our systems often fall short because they lack adaptability to feedback. To address this, we are building a continual learning infrastructure that captures context, memory, and decision-making processes throughout the enterprise, enabling specialized agents to effectively execute real tasks.What Excites Us: We operate at a unique intersection where our product team constructs the platform that fuels a new generation of digital coworkers. Our research team pushes the boundaries of post-training and reinforcement learning, creating innovative product experiences. Our applied research engineers collaborate closely with clients to deploy models into production. This blend of strong product focus, deep research, and hands-on customer engagement is crucial for integrating AI into the enterprise. We are product-driven, research-informed, and actively engaged with our clients.Our Team: Our diverse team consists of engineers, researchers, and operators, many of whom are former founders. We have built RL infrastructure at leading organizations like OpenAI and Scale AI, and developed systems at Together, Two Sigma, and Watershed. We proudly serve Fortune 50 clients alongside companies like DoorDash, Mercor, and Cognition. Our work is supported by renowned investors, including Benchmark, Sequoia, and Lux.Who Thrives in Our Environment: We seek individuals eager to apply cutting-edge research and complex systems to tackle real-world challenges. You should be adept at quickly adapting to new environments, whether it’s a fresh codebase, a client’s data architecture, or an unfamiliar problem domain. A genuine enjoyment of customer interactions—listening, empathizing, and understanding how tasks are accomplished within their organizations—is essential. Those with entrepreneurial backgrounds, extensive side projects, or demonstrated end-to-end ownership typically excel in our company.

Join Our Team at MacroscopeAt Macroscope, we are dedicated to being the definitive source of truth for any software development company. Our mission is to empower leaders with clarity and provide engineers with the time they need to innovate.We enable leaders to gain insights into the evolution of their products and codebases—tracking changes, understanding team contributions, and identifying progress—all grounded in the ultimate source of truth: the code itself.Founded by experienced entrepreneurs who have successfully built and sold multiple companies, and held executive positions in public tech firms, we are backed by top-tier venture capital firms such as Lightspeed Venture Partners, Thrive Capital, Google Ventures, and Adverb.The RoleWe are seeking a Senior Applied Machine Learning Engineer who will be responsible for designing, developing, and optimizing the ML and AI systems that drive our core offerings. You will have full ownership of the systems, overseeing everything from data collection and evaluation to model experimentation and large-scale production deployment.This cross-functional position entails leading the ML/AI lifecycle for one of our most vital features: AI Code Review. Collaborating closely with our co-founders, you will make pivotal decisions that shape our product's development—ranging from building high-quality datasets to interpreting experimental results and enhancing model performance architecture. Additionally, you will play a significant role in crafting and implementing software that seamlessly integrates our models with our backend applications and user experience, offering a unique opportunity to influence our product's evolution significantly.Technology Stack: Typescript/React (frontend), Golang (backend), Temporal, Google Cloud (GCP), Postgres, Terraform, and custom-built AST "code walkers" in several programming languages including Golang, Typescript, Swift, Python, and Rust.

ABOUT USAt Applied Compute, we are pioneers in developing Specific Intelligence for enterprises, creating agents that learn continuously from a company’s processes, data, expertise, and objectives. Our mission is to establish a continual learning platform that captures context, memory, and decision traces throughout the organization, enabling specialized agents to perform meaningful tasks.Why Join Us: Our team operates at a unique intersection of innovation. Our product team is responsible for crafting a platform that serves as the backbone for a new generation of digital coworkers. Meanwhile, our research team explores the cutting edge of post-training and reinforcement learning to enhance product experiences. Our applied research engineers collaborate closely with clients to deploy agents effectively in real-world scenarios. This synergy of robust product development, extensive research, and direct client engagement is essential for us to revolutionize AI in the enterprise landscape.Our Team: Comprising engineers, researchers, and operations experts, our team includes many former founders with extensive experience. We have developed RL infrastructure at OpenAI, data foundations at Scale AI, and other systems at companies like Two Sigma and Watershed. We proudly serve Fortune 50 clients and are supported by top-tier investors including Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.Who Thrives Here: We seek individuals passionate about utilizing cutting-edge research and complex systems to address real-world challenges. Comfort navigating diverse environments, whether it’s a new codebase, unfamiliar customer data architecture, or unexplored problem domains, is essential. Our team values genuine client engagement — listening, empathizing, and understanding the realities of work in their organizations. Those with entrepreneurial spirits, rich project experiences, or proven capabilities to manage tasks end-to-end will excel in our environment.THE POSITIONAs a Software Engineer, you will be instrumental in building the products and interfaces utilized by customers and internal teams. You will manage the entire application platform stack, from collaborative human-AI workspace systems to backend workflows orchestrating sandboxed agent sessions, and the continual learning SDK that provides engineers with oversight of the agent development lifecycle.

About UsAt Speak, our mission is to revolutionize language learning.Learning a new language can transform lives by unlocking opportunities in diverse cultures, careers, and communities. With over two billion individuals around the globe striving to learn a language, we recognize that traditional one-on-one tutoring remains difficult to access at scale and has seen little innovation over recent decades. Speak is pioneering an AI-driven, human-level tutor accessible right from your pocket, providing a conversation-first experience where learners can practice speaking, receive immediate feedback, and progress through meticulously crafted lessons. Our goal is to facilitate a comprehensive journey from beginner to proficient speaker across various languages.Launched in South Korea in 2019, Speak has quickly become the leading language learning app in the region, now reaching learners across numerous markets and offering instruction in 15+ languages. Supported by over $150 million in venture capital from prestigious investors such as OpenAI, Accel, Founders Fund, and Khosla Ventures, our team is distributed across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana.Role OverviewWe are seeking a skilled Machine Learning Engineer specializing in speech to join our innovative team. In this role, you will take charge of the entire modeling pipeline for speech recognition, encompassing training, experimentation, deployment, and ongoing monitoring. Collaborating closely with Product teams, you will design cutting-edge learning experiences and assess the effectiveness of production models on our users. As part of a nimble and dynamic team, you'll contribute as both a developer and a thought partner on projects related to ASR, assessments, pronunciation improvements, content personalization, and more. This is an exhilarating opportunity to be part of an ML team focused on crafting personalized learning experiences that will transform language education for millions worldwide.

Join David AIAt David AI, we are pioneering the audio data research landscape. Our research and development approach to data ensures that we deliver datasets with the same precision and rigor that leading AI labs apply to their models. Our mission is to seamlessly integrate AI into everyday life, leveraging audio as a key channel. As we witness advancements in audio AI and the emergence of new use cases, we recognize that high-quality training data is the critical component. This is where David AI steps in.Founded in 2024 by a group of former engineers and operators from Scale AI, we have rapidly established partnerships with major FAANG companies and AI labs. Recently, we secured a $50M Series B funding round from prominent investors including Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, and First Round Capital.Our team is sharp, humble, and ambitious. We are on the lookout for talented individuals in research, engineering, product management, and operations to join us in our mission to redefine the audio AI landscape.About Our Machine Learning TeamOur Machine Learning team operates at the forefront of innovative research and practical application, transforming raw audio into high-quality data for top AI labs and enterprises. We manage the entire machine learning lifecycle—from exploring novel speech processing algorithms to deploying models that handle terabytes of audio data daily.Your RoleAs an Applied ML Engineer at David AI, you will develop state-of-the-art speech and audio models, establish production inference systems, and create robust pipelines that demonstrate the true potential of high-quality data.Key ResponsibilitiesResearch and Design: Create solutions using advanced signal processing algorithms and cutting-edge ML models tailored for speech and audio applications.Development: Build production-grade inference algorithms, pipelines, and APIs in collaboration with cross-functional teams to extract valuable insights for our clients.Collaboration: Work alongside our Operations team to gather valuable training and evaluation datasets to enhance our model quality.Architecture: Design systems that ensure durable and resilient inference and evaluations.

Job DescriptionEmbrace the future of competitive advantage with Eragon, where we create bespoke AI systems that are meticulously tailored to understand your unique business landscape.At Eragon, we focus on developing AI models that leverage proprietary data, deployed directly within customer environments and continuously refined through real-world interactions. Our models not only respond but evolve, improving with each user engagement.We utilize a cutting-edge reinforcement learning framework known as RLQF (Reinforcement Learning from Query Feedback) that transforms user interactions into valuable training signals, establishing a cycle of ongoing enhancement that surpasses traditional fine-tuning methods.The RoleAs an Applied Research Engineer, you will be responsible for designing, training, and deploying advanced models that drive real business operations.This position is not about theoretical research; you will engage directly with customer data, constraints, and feedback, crafting solutions that excel in production settings. You will manage the entire lifecycle of the project, from defining the problem and designing data structures to training, evaluating, and iterating based on live performance.What You’ll DoTrain and adapt models: Fine-tune and post-train models on customer-specific data utilizing RLQF among other techniques.Close the loop: Convert real user interactions, corrections, and workflows into actionable training signals.Own end-to-end systems: Oversee the process from data ingestion and curation through to training, evaluation, and deployment.Evaluate in production: Create evaluation frameworks that accurately reflect real-world performance, rather than relying solely on benchmarks.Work with customers: Collaborate closely with users to comprehend their workflows and translate these into model functionalities.Ship and iterate: Focus on the continuous improvement of models based on live feedback and measurable outcomes.What We’re Looking ForExtensive hands-on experience in training, fine-tuning, or post-training machine learning models.Proficiency in handling messy, real-world data as opposed to only clean benchmarks.Familiarity with reinforcement learning techniques, feedback-driven training such as RLHF or RLAIF, and evaluation systems.Adeptness at quickly transitioning from problem identification to data management, model development, and iterative improvement.Strong engineering instincts with a comfort level in managing systems end-to-end.A proactive approach to shipping and enhancing systems, rather than solely focusing on research.

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 fal, we are crafting the foundational infrastructure for the generative AI era. Our mission is to empower developers and enterprises to effortlessly create, deploy, and scale multimodal AI applications with unparalleled speed, simplicity, and reliability. By merging high-performance inference, orchestration, and observability into a single cohesive platform, fal enables organizations to introduce innovative AI products without the burden of managing complex infrastructures.With swift adoption across various industries and a market poised for explosive growth projected to reach hundreds of billions in the coming decade, fal stands uniquely positioned to play a pivotal role in the next wave of AI innovation.About The Rolefal is transforming the creative technology stack for the Generative Media age. We are on the lookout for a dynamic Commercial (Mid-Market) Account Executive to join our expanding team and assist clients in harnessing the power of AI for media generation, automation, and scalability.If you excel in high-energy environments, enjoy collaborative work, and are driven by the desire to help companies innovate through technology, this role presents an exhilarating chance to be part of the future of AI infrastructure.Technologies You'll UseSalesforce, Outreach, Gong, Clari, Apollo, fal Console.Your ResponsibilitiesIdentify and engage with target mid-market accounts to generate qualified opportunities and ensure consistent pipeline growth.Utilize marketing-generated leads alongside outbound strategies to create demand for fal’s Generative Media infrastructure.Collaborate with creative studios, AI innovation teams, and AI developers to uncover new adoption opportunities.Execute each sales cycle meticulously: conduct discovery sessions, lead product demonstrations, align with executives, and deliver business outcomes that enhance long-term customer value.Develop a robust understanding of fal's Generative Media platform, its technical framework, and its value across various industries.Implement strategic campaigns to promote customer adoption and expand usage within accounts during the initial 6–12 months post-sale.Accurately forecast and manage pipeline utilizing MEDDPICC and Command of the Message methodologies.Work cross-functionally with marketing, product, and engineering teams to gather insights and inform go-to-market strategies.Adapt and excel in a rapidly evolving market, continually learning and innovating to meet customer demands.What We’re Looking ForExperience in sales, particularly in a technology-focused environment, is preferred.

Join fal as a Software Engineer and play a crucial role in developing the next generation of usage-based billing systems. This is an exciting opportunity for individuals who are enthusiastic about designing scalable, event-driven systems that seamlessly integrate with Stripe and Orb, enabling real-time usage tracking and delivering precise, adaptable billing experiences for our clients. In this position, you will collaborate closely with cross-functional teams, including Product, Finance, and Infrastructure, to ensure our billing system is reliable, accurate, and capable of accommodating evolving pricing models as our product offerings expand.

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.