Machine Learning Fellow Jobs

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: We’re seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You’ll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences. RESPONSIBILITIES: Designing and architecting recommendation algorithms across various product surfaces Leverage all of SpaceXSI's infra and AI stacks to dramatically enhance the user experience Write data pipelines and training jobs that continuously learn from product data. Iterate and improve the algorithm by gathering user feedback in real time through experimentation Ensuring scalability and efficiency of machine learning systems BASIC QUALIFICATIONS: Knowledge of data infrastructure like Kafka, Clickhouse, and Spark Experienced in implementing recommender systems and/or deep learning applications at industrial scale Skilled in one or more DL software frameworks such as

Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking. Responsibilities Relentlessly push search quality forward—through models, data, tools, or any other leverage available Architect and build core components of our search platform and model stack Train and evaluate retrieval, ranking and classification models, including LLMs Deploy models - from boosting to LLMs - in a scalable and performant way Build and optimize RAG pipelines for grounding and answer generation Collaborate with Data, AI, Infrastructure and Product teams to ensure fast and high quality delivery Qualifications Deep understanding of search and retrieval systems, including quality evaluation principles and metrics Proven track record with large-scale search or recommender systems Self-driven, with a strong sense of ownership and execution Minimum of 5 years of working on search or recsys-related projects

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a C++ Machine Learning Engineer on the AI Models team at Tenstorrent, you’ll work on the training framework behind our most advanced models. You’ll write high-performance C++ code, shape how new layers and operators are implemented, and help models scale across our custom silicon. If you enjoy building the guts of ML systems and seeing them run fast, this role is for you. This role is hybrid, based out of Warsaw or Gdansk, Poland. We also consider remote candidates within Poland on a case-by-case status. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are Strong in C++ and low-level systems programming, especially in performance-critical code. Comfortable thinking in tensors, memory layout, and compiler graphs. Familiar with PyTorch and curious about how frameworks map to hardware. A builder who enjoys solving technical puzzles and digging into the details. What We Need Extend and optimize our ML training framework with new ops, layers, and training features. Debug and tune model performance on Tenstorrent chips. Work with compiler and kernel teams to make sure models compile and run as expected. Support integration of real-world models

JOB DESCRIPTION Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES Students enrolled in a PhD program in machine learning, computer science, statistics, or a related field. Superb analytical and quantitative skills, along with a healthy streak of creativity. Demonstrated ability to conduct independent research utilizing large data sets. Passion for seeing research through from initial conception to eventual application. Curiosity about financial markets Strong scientific programming in Python, R or Matlab. Empirical, detail-oriented mindset. Sense of ownership of his/her work, working well both independently and within a small collaborative team. We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you’ve worked outside of school, or as part of your curriculum. If you’re proud of the work you did we want to hear abou

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. What you’ll do: Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas Use data driven methods and leverage the unique properties

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . With more than 600 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. Within the EPD (Engineering, Product, and Design), Ads ML Engineering team connects the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads. What you’ll do: Build cutting edge technology using the latest advances in deep learning and machi

About the Role Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI! Responsibilities Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale. Develop and optimize runtime inference services for large-scale AI applications. Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world. Conduct design and code reviews to ensure high standards of quality. Create services, tools, and developer documentation to support the inference engine. Implement robust and fault-tolerant systems for data ingestion and processing. Requirements 3+ years of experience writing high-performance, well-tested, production-quality code. Proficiency with Python and PyTorch. Demonstrated experience in building high performance libraries and tooling. Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale. Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum Preferred: Knowledge of AI inference techniques such as speculative decoding. Preferred: Knowledge of CUDA/Triton programming. Nice to have: Knowledge of Rust, Cython and compilers. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference th

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors At Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform, including newsfeed, notifications, ad relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be integral to making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make You will be part of a scrappy and

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The mandate of the learned behavior team is to use advanced machine learning techniques to accelerate software progress. In this role, you will work closely with the software vertical teams to understand their pain points and explore novel and advanced machine learning methods to solve practical real-world challenging problems. To name a few, using self-supervised learning to learn robust representations, exploring techniques for out-of-distribution detection to solve long tail problems, adjusting reinforcement learning techniques for motion planning, working on trajectory prediction and motion planning, investigating the robustness of models to mitigate uncertainties, or trying to build an end-to-end driving system. If you love solving challenging new problems with a mindset of deriving practical solutions to eventually be used on the vehicle, come join us! About the Work Work on scalable machine learning based planning and pre

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Work Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation. Build generative models with foundation models. Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation. Optimize generative models using reinforcement learning to improve interactive reasoning. Explore reward modeling/learned verifier using generative models. Explore joint prediction and planning and self-play. Leverage generative models for active learning and world modeling. Develop controllable generative models to guide the generation process towards desired goals, conditions and rewards. Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them, evaluate

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job Key Focuses: Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices an

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job Key Focuses: Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices an

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: At ZipRecruiter, where a universe of data, brimming with over a billion archived job postings, tens of millions of dynamic job seekers, and countless impression and click events, there’s plenty of opportunities for innovation. Here, your experience will be put to work crafting new, data-driven features that impact the lives of millions, connecting them to their dream jobs. We're tackling exciting challenges: imagine developing a system that can predict salaries for new job postings, using a training set of job postings and known salaries. But the fun doesn't stop at model-building. Our work involves an immersive dive into data - gathering, cleaning, analyzing, and extracting meaningful insights. Key Focuses: Design, develop, and maintain machine learning models and algorithms to solve complex business problems Identify patterns, trends, and anomalies in the data, and visualize insights using appropriate tools Assess the performance of machine learning models using appropriate metrics, validation techniques, and testing datasets Discover opportunities to optimize models by fine-tuning hyperparameters, feature selection, or employing regularization techniques to improve accuracy, performance, and scalability Minimum Qualifications: 3+ year of professional software development experience with a focus in machine learning Deep experience i

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: At ZipRecruiter, where a universe of data, brimming with over a billion archived job postings, tens of millions of dynamic job seekers, and countless impression and click events, there’s plenty of opportunities for innovation. Here, your experience will be put to work crafting new, data-driven features that impact the lives of millions, connecting them to their dream jobs. We're tackling exciting challenges: imagine developing a system that can predict salaries for new job postings, using a training set of job postings and known salaries. But the fun doesn't stop at model-building. Our work involves an immersive dive into data - gathering, cleaning, analyzing, and extracting meaningful insights. Key Focuses: Design, develop, and maintain machine learning models and algorithms to solve complex business problems Identify patterns, trends, and anomalies in the data, and visualize insights using appropriate tools Assess the performance of machine learning models using appropriate metrics, validation techniques, and testing datasets Discover opportunities to optimize models by fine-tuning hyperparameters, feature selection, or employing regularization techniques to improve accuracy, performance, and scalability Minimum Qualifications: 3+ year of professional software development experience with a focus in machine learning Deep experience i