Machine Learning Fellow Jobs

We are looking for a Senior/Staff Software Engineer to lead the development and scaling of our cloud services and APIs that handle ride hailing for Zoox’s production-grade robotaxi service. These services include dispatch, routing, payments, mobile APIs, telemetry processing, service metrics and more. In this role, you will: Design and build scalable, efficient, and robust backend systems for Zoox’s ride-hailing service Own core functionality such as payments, fleet dispatch, service management Make significant contributions to technical roadmaps, development plans and execute on them effectively. Uphold engineering excellence by demonstrating best practices in software development including design review, code review, software testing and documentation. Qualifications 8+ years of cloud software experience Experience running and optimizing production-grade systems for maximum efficiency and resilience. Extensive experience with the design, implementation and operation of backend microservices. Proficiency with Kotlin or Java, REST APIs and SQL. Experience running production services using cloud infrastructure such as Kubernetes and Docker Bonus Qualifications Experience with Spring Boot based microservice architectures, PostgreSQL, Elasticsearch Experience in transportation, robotics, logistics, or autonomous vehicles. Experience with event driven architecture and Kafka. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you nee

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Auth0 provides an unparalleled authentication experience for hundreds of millions of users worldwide. Our commitment to reliability is a key foundation of our product and our dedication to exceeding customer availability expectations is a core engineering focus. As a Senior Site Reliability Engineer, you'll join our SRE team based in Europe to ensure our production systems are not only operational but also resilient, scalable, and ready for exponential growth. This isn't just about keeping the lights on; it's about directly contributing to the platform's core resiliency and robustness. You'll be a hands-on builder, crafting solutions that make our system more reliable by design. What you’ll do: Design and build custom software in Go to enhance the platform's reliability, resiliency, and redundancy. Partner with engineering teams to embed reliability principles, improving the availability, performance, and observability of our services. Use your deep understanding of infrastructure and observability principles to identify opportunities for improvement within the product and implement solutions. Contribute to our follow-the-sun on-call rotation, providing rapid, effective response to critical incidents and using your expertise to troubleshoot, mitigate or accurately escalate production issues. Because our team is globally distributed, your on-call shifts will only occur during your standard local working hours. Develop and refine our SRE tooling and proc

🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts , accounts for 16-17 year olds , a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save , invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo ❤️ 📍London / UK Remote | 💰 Staff Backend Engineer (L60) £130,000 - £170,000 + Equity + Benefits | Technology - Engineering About our Engineering Teams: We have around 650 engineers out of roughly 5,500 people in total - and we have big ambitions. There are many interesting challenges ahead, and we're happy for people to move between teams or to specialise, whatever you prefer. As an engineer here you'd be able to work directly with anyone across the company, and we run regular knowledge-sharing sessions so you’ll learn heaps about everything from how banks work to effective communication. We contribute to open source software as much as possible. Our blog is a good place to learn even more about what we do! What you’ll be working on: We rely heavily on the following tools and technologies: Go to write our application code (there’s an excellent interactive Go tutorial here ) Cassandra for most persistent data storage Kafka for our asynchronous message queue Envoy Proxy for RPC Kubernetes and Docker to schedule and run our services AWS for most of our infrastructure React for internal web dashb

P-225 Location: Toronto Only As a Solutions Architect at Databricks within the Field Engineering org you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge and can drive complex technology discussions which express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customer's needs and build valuable customer engagements and report to the Field Engineering Manager. The impact you will have: You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform. Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning. You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases. Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications. Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars. What we look for: 5+ years in a customer-facing pre-sales, technical architecture, or consulting role with expertise in at least one of the following technologies: Big data engineering (Ex:

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to seek, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. What you’ll be doing: Working closely with product design engineers, you'll perform PCB layout of high speed/high-density value-conscious PCBs for all business units at NVIDIA (GPU Desktop, Notebook, Automotive, Professional, Data Center, Deep Learning, and AI), all using Cadence PCB design tools. Focus will be on the complete development of CAD layout from symbol creation, floor planning, and detailed component placement, constraints management, with a concept of topology and signal/trace integrity. You will be responsible for the design releases required generation of artwork files, ODB++, and electronic PCB documentation. Your designs will need to follow SI constraints, EMI/RFI control and FCC, UL and European regulations, IPC specifications and NRC regulations. What we need to see: B.Sc. in Electronic Engineer degree or equivalent experience. 5+ years of experience in high-speed design. Having a detailed knowledge of circuit design and consideration for layout, routing, and timing constraints, DFM, DFA, DFT constraints in volume manufacturing is needed for this role. Be an authority in using Cadence Allegro PCB design tools. Have a deep understanding of High-Density Interconnect PCB layout and PCB Signal Integrity. Knowledge in PCB ma

Cote Korean Steakhouse, located in the Miami Design District, is the carnivorous vision of proprietor Simon Kim that blends together the dining experience of Korean Barbeque together with the hallmarks of a classic American Steakhouse. Cote serves the highest quality USDA Prime beef accompanied by an impeccable 1200+ label wine list and a suite of classic-but-creative cocktails. We are professionals committed to ensuring exceptional hospitality and service to our customers. At COTE, we follow a simple mantra: 🥩 + 🔥 + 🍸 = 😊 Essential Job Duties & Responsibilities: Job duties and responsibilities include, but are not limited to the following: Receives all clean glassware, flatware, plate ware, and other service equipment from the Porters in the dish pit and inspects for flaws before polishing. Removes cracked or defective items from service and informs management. Polishes all clean glassware, flatware, plate ware, and other service equipment to a perfect shine. Ensures no watermarks, stains, lint, or other debris remain on product. Regularly polishes and maintains metallic grill rims, grill equipment, and kitchen pots and pans using metal polish. Maintains cleanliness and appearance of the dish pit area at all times. Daily cleaning of ice machines, coffee station, water station, and refrigerators. Completes all assigned side work related to set up and breakdown of dish pit area. Maintains all tools of the position including specialty glass polishing cloths. Reports to each scheduled shift on time, in uniform, and ready to work. Responsible for training new employees as assigned. Assists other stations or areas of the restaurant when requested by management. Standards: Display knowledge of Cote brand, culture, and product. Demonstrate the Company’s core values of people, learning, culture, relationships, sustainability and stewardship. Maintain professional and respectful behavior when in contact with customers , management,

Position: Mechanical Engineer Location: Austin, Texas Job Overview: Infinitum is looking for a full-time Mechanical Engineer to work on site in our fan engineering team. In this role you will be a key contributor in developing proprietary commercial and industrial fan systems for Infinitum. Key Responsibilities: Conduct product design and development following general design guidelines and tools including CAD programs. Conduct calculations and analysis using closed-form methods, computer applications, and FEA and other simulation tools. Develop calculation tools for specific problems. Support other departments and customers by addressing technical questions under general design guidelines. Review drawings, schematics, bills of material, and other documentation necessary to manufacture, test, install, and commission products. Create and enhance specific design guidelines by leveraging past experience and technical learning. Develop new products by providing input on specifications, designing and building prototypes, devising validation tests, and preparing supporting documentation. Provide input to project feasibility and cost analysis. Participate in product improvement, productivity improvement, standardization, cost reduction, and cycle time reduction initiatives. Lead some of these initiatives. Provide disposition to non-conformances and participate in corrective actions providing technical input based on established design guidelines. Qualifications and Skills Must-Have Skills: Bachelor's degree (B.S.) from a four-year college or university in Engineering or Physical Science with 4+ years of related work experience, or an equivalent combination of education and experience. Basic design knowledge of machined components, sheet metal parts, castings, and injection molded components. Proficiency in SolidWorks (CSWP preferred), including sheet metal design and generating manufacturing drawings. Understanding of ASME Y14.5 GD&T and how to apply

At Scale , our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's Machine Learning Research team builds the foundation for the next generation of AI systems — pushing the boundaries of what's possible with frontier models while ensuring safety, reliability, and alignment at every step. Our work spans generative AI, reinforcement learning and advanced post-training methods, scalable oversight, synthetic data pipelines, red teaming, and evaluation science. We are developing a large-scale hybrid human-machine system to power machine learning pipelines for dozens of industry-leading customers. These models and systems form the backbone of Scale's long-term strategy, enabling billions of tasks monthly and supporting some of the most complex and advanced use cases in the AI ecosystem. As an intern, you'll work on a combination of deeply technical ML applications in production and cutting-edge research problems, with mentorship from world-class researchers and the opportunity to collaborate with leading teams across industry and academia. Interns own real, published or shipped work — not side projects. Example Projects Measure the dangerous capabilities of frontier models and conduct preparedness research Research the science and creation of new benchmarks for frontier models Develop new methods for training models to excel on extremely difficult reasoning problems that require long chains of thought Research reinforcement learning and post-training methods that improve model reliability on high-stakes tasks Research scalable oversight protocol

Machine Learning Development Intern Description - Description: The main objective of this internship program is to train and develop students to contribute to cutting-edge projects in Machine Learning (ML), and Generative AI (GenAI). Interns will take responsibility for key aspects of ongoing projects, gaining hands-on experience in ML model development and deployment. They will be involved in training, collaborative work, and practical tasks aimed at enhancing their skills in a corporate environment focused on innovation in AI. Role: Support the development of ML models, with a focus on Generative AI and Prompt Engineering; Assist the ML team in fine-tuning models, optimizing prompt inputs, and improving output quality for AI-driven applications; Collaborate with engineers and data scientists to understand project requirements and provide solutions for building and deploying AI-based chatbots and applications; Participate in technical meetings and brainstorming sessions to improve model performance; Research the latest trends and breakthroughs in GenAI and contribute to experimentation with new techniques; Help document the development process, maintaining quality standards and best practices in model iteration and deployment. Qualifications: Students in Computer Science / Data Science / Machine Learning / Artificial Intelligence / Engineering or related fields from the 2nd semester onwards; Knowledge of machine learning algorithms, deep learning, natural language processing (NLP), and AI model architectures; Strong interest in Generative AI, chatbot development, and prompt engineering; Basic experience with Python, TensorFlow, PyTorch, or other ML frameworks; Curiosity about cloud computing, large language models (LLMs), and AI-driven soluti

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Key Responsibilities Build and facilitate machine learning and Generative AI solutions across large-scale systems and campaigns, ensuring deployment and updates in collaboration with data engineering. Develop and participate in presentations and consultations to existing and prospective stakeholders on analytics results and solutions. Collaborate with internal and external peers and managers to exchange complex information related to areas of specialization. Required Qualifications Experience in building end-to-end machine learning models and data-intensive systems in production (2 or more years or PhD with a tech internship as MLE/Software Developer). Strong background in Data Science with a focus on software development best practices (2 or more years or PhD with a tech internship as MLE/Software Developer). Proficiency in Python, SQL, and MLOps (3 or more years or PhD with a tech internship as MLE/Software Developer). Experience in cloud environments (3 or more years as MLE/Software Developer). Preferred Qualifications Demonstrated ability to design and build distributed data-intensive products; front-end development and coding in React is a plus. Experience with Google Cloud Platform (GCP) (2 or more years) is a major plus. Familiarity with Generative AI and agentic design is

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. As a Machine Learning Engineer on our team, you will be at the forefront of developing high-quality, production-ready models that play a central role in our decision-making processes. Your contributions will be instrumental in shaping our financial landscape. If you have a strong interest in machine learning and enjoy challenging work, Affirm is the place for you! What you'll do Use Affirm’s proprietary and other third party data to develop machine learning models that predict the likelihood of default and make an approval or decline decision to achieve business objectives Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems Research ground breaking solutions and develop prototypes that drive the future of credit decisioning at Affirm Implement and scale data pipelines, new features, and algorithms that are essential to our production models Collaborate with the engineering, credit, and product teams to define requirements for new products What we look for 2+ years of experience as a machine learning engineer or PhD in a relevant field Proficiency in machine learning with experience in areas such as Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration. Domain knowledge in credit risk is a plus Strong engineering skills in Python and data manipulation skills like SQL Experience using large scale distributed systems like Spark or Ray Experience using open source projects and software such as scikit-learn, pandas, NumPy, XGBoost, Kubeflow Experience developing machine learning models at scale from inception to business impact Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams The ability to

At NVIDIA, we’re building GeForce G-Assist — an on-device AI assistant that combines Small Language Models (SLMs), retrieval systems, and hybrid cloud capabilities to deliver responsive, context-aware assistance inside the GeForce ecosystem. We work closely across engineering and product teams to ensure G-Assist performs reliably in real-world scenarios. What you'll be doing: Together, we focus on how models behave in production, not just on benchmarks. Evaluate and improve Small Language Models used in GeForce G-Assist, with an emphasis on accuracy, robustness, and conversational reliability. Identify and mitigate conversation and context contamination, including state drift, prompt leakage, and retrieval cross-talk. Work with SLM and VLM architectures to support text and multimodal interactions. Collaborate on hybrid architectures that combine local SLMs with cloud-based models. We value engineers who enjoy thinking across the full system—from model behavior to runtime performance. Optimize local inference using llama.cpp, including quantization, memory usage, and performance tuning. Read, write, and optimize C/C++ code in performance-critical paths. Design and integrate retrieval-augmented generation (RAG) systems that ground responses in system and user context. Support agentic AI workflows, enabling planning, tool use, and multi-step execution. What we need to see: 5+ years of validated experience in system software or a related field, with an M.S. or higher degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience). We’re looking for teammates who enjoy solving real problems, learning as they go, and collaborating in a tight-knit environment. Strong ability to read and write C/C++ code in systems-level or performance-sensitive environments, along with proficiency in Python. Hands-on experience w

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Software Engineer, ML Platform, you will work on our ML Data Team and be instrumental in architecting, implementing, and maintaining foundational ML infrastructure powering Feeds Ranking, Content Understanding, Recommendations, Ads, and much more to fulfill Reddit’s mission of bringing community and belonging to everyone in the world. You will create ML data-governance tools that help MLEs discover and reason about signals, while contributing across the broader ML data platform—including prediction logging and training data systems. Lead the design, development, testing, and operation of ML signal-governance capabilities that help MLEs discover signals and understand their ownership, lineage, quality, and usage. Build tools that help teams assess signal importance and make informed lifecycle decisions. Partner with MLEs and cross-functional teams to define governance workflows and deliver reliable, intuitive ways to explore and act on signal metadata. Contribute across the ML Data Platform, including prediction logging and training data platforms, to design, develop, test, and operate batch and streaming pipelines processing petabyte-scale data. Drive complex projects end to end from technical planning an

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing. The Opportunity at Altana We're looking for a Senior Staff Machine Learning Engineer to lead the AI behind Altana Nexus, our agentic platform for global trade. You'll work on a continuous stream of public and proprietary trade data (shipments, customs filings, trade documents), and build the models and AI agents that turn it into real-time decisions on risk, compliance and enforcement for governments and the world's largest companies. Your Responsibilities Drive the technical direction for agentic systems. Define the architecture and roadmap for the models and agentic systems that process trade data as it arrives (shipments, customs declarations, invoices, bills of lading) and turn it into risk, classification and compliance decisions in real time. Build the pipeline from ingestion to decision. Lead the design of reliable, cost-efficient systems for ingestion, document understanding, entity resolution, inference and routing across models, at the scale of global trade. Adapt models to trade. Use analyst feedback, production outcomes and agent traces to fine-tune and post-train models (SFT, DPO, RL with domain graders) where it measurably beats prompting, and keep every model improving over time. Design the observability and feedback stack. Build the evals, tracing and feedback loops that decide what ships and catch regressions in production. Lead beyond your team. Mentor senior engineers, raise the technical bar across Engineering, and help shape how we hire and level ML talent. Shape the product and the business. Work with software engineers, data scientists, product managers and customers to generate new business ideas and turn ambiguous problems into shipped capabilities. About You BS/MS in Computer Science, Machine Learning, or a related field, or equivalent experi