Machine Learning Fellow Jobs

FEQ425R228 As a Solutions Architect, you will shape the future of the Data & AI landscape by working with the most sophisticated data engineering and data science teams in the world. You will be a technical advisor internally to the sales team, and work with the product team as an advocate of your customers in the field. You will help our customers to achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. You'll grow as a leader in your field, while finding solutions to our customers' biggest challenges in big data, analytics, data engineering and data science problems Reporting to the Field Engineering Manager, you will collaborate with our most strategic prospects and customers, work directly with product and engineering to drive the Databricks roadmap forward, and work with the broader customer-facing team to develop architectures and solutions using our platform. You will guide customers through the competitive landscape, best practices, and implementation, and develop technical champions along the way. This is a Hybrid role, based in Mumbai. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. You will work directly with the sales team to develop your book of business, define account strategies, and execute those strategies to help your customers and prospects solve their business problems with Databricks. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and o

FEQ327R210 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world. Reporting to the Field Engineering Manager, you will collaborate with existing DNB customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and our users Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community. What we look for: 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role Experience building distributed data systems Comfortable programming in, and debugging, Python and SQL Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in one of the following: Data Engineering technologies ( Ex: Spark, Hadoop, Kafka ) Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, pytorch,

As a Sr. Solutions Architect on the team supporting the strategic Digital Natives Business (DNB) customers, you will shape the future of the Data & AI landscape by working with the most sophisticated data engineering and data science teams in the world. Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation, and develop technical champions along the way. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. Lead technical discovery and design architectures, implement proof of concepts for strategic projects spanning data engineering, data science and machine learning, and SQL analysis workflows. You will also help customers build solutions that integrate with cloud services, home grown tools, and other 3rd party applications. Act as strategic technical advisor to customers to help them drive business outcomes. Collaborate with your fellow Solutions Architects, using your skills to support each other and our users. Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, MLflow, Omnigent) across the developer community. What we look for: 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role Experience building distributed data systems Comfortable programming in and debugging Python and SQL Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in one of the following: Data Engineering technologies ( Ex: Spark, Hadoop, Kafka ) Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, PyTorch, Tensorflow ) Available to travel to customers in yo

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. Role Overview We are seeking a Senior Software Engineer to build and evolve Okta’s web platform using React and Next.js. In this role, you will bring deep frontend expertise to solve complex engineering problems autonomously from designing scalable page systems and optimizing performance to integrating CMS APIs and refining developer workflows. You work independently on ambiguous problems but thrive in collaboration with designers, content architects, and fellow engineers. AI-assisted development tools are part of how this team works, and you leverage them fluently to move faster while maintaining high standards. This is a hands-on IC role with significant autonomy and real ownership, ideal for an engineer who combines deep technical understanding with strong collaborative instincts. Key Responsibilities Frontend Development & Architecture: Build and maintain reusable page templates, features, and component systems in Next.js using TypeScript and React. Design scalable data-fetching patterns from headless CMS APIs (GraphQL and REST), transforming structured content into polished frontend experiences. Collaborate on content model design with content architects, ensuring CMS data maps cleanly to frontend templates. Implement responsive, accessible, high-performance UI following established design system patterns and propose improvements when existing patterns fall short. Design System Collaboration: Work closely with the design system team to assemble pag

FEQ427R107 As a Solutions Architect, you will shape the future of the Data & AI landscape by working with the most sophisticated data engineering and data science teams in the world. You will be a technical advisor internally to the sales team, and work with the product team as an advocate of your customers in the field. You will help our customers to achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. You'll grow as a leader in your field, while finding solutions to our customers' biggest challenges in big data, analytics, data engineering and data science problems Reporting to the Field Engineering Manager, you will collaborate with our most strategic prospects and customers, work directly with product and engineering to drive the Databricks roadmap forward, and work with the broader customer-facing team to develop architectures and solutions using our platform. You will guide customers through the competitive landscape, best practices, and implementation, and develop technical champions along the way. This is a Hybrid role, based in Delhi. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. You will work directly with the sales team to develop your book of business, define account strategies, and execute those strategies to help your customers and prospects solve their business problems with Databricks. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and ou

FEQ227R53 As a Senior Solutions Architect, you will shape the future of the Data & AI landscape by working with the most sophisticated data engineering and data science teams in the world. You will be a technical advisor internally to the sales team, and work with the product team as an advocate of your customers in the field. You will help our customers to achieve tangible data-driven outcomes through the use of our Databricks Lakehouse Platform, helping data teams complete projects and integrate our platform into their enterprise Ecosystem. You'll grow as a leader in your field, while finding solutions to our customers' biggest challenges in big data, analytics, data engineering and data science problems Reporting to the Field Engineering Manager, you will collaborate with our most strategic prospects and customers, work directly with product and engineering to drive the Databricks roadmap forward, and work with the broader customer-facing team to develop architectures and solutions using our platform. You will guide customers through the competitive landscape, best practices, and implementation, and develop technical champions along the way. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. You will work directly with the sales team to develop your book of business, define account strategies, and execute those strategies to help your customers and prospects solve their business problems with Databricks. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and our users Become an expert in, pro

1KOMMA5° At 1KOMMA5° , we pursue a clear vision: Living on wind and sunlight forever for free . To make this a reality, we are building the energy system of the future with Heartbeat AI. Want to be part of it? We bring together regional craftsmanship and scalable software: We don't think of solar, batteries, heat pumps, and e-mobility as isolated components, but control them as an intelligent, integrated overall system in our virtual power plant. Directly connected to the electricity market – in real time, fully automated. This way, energy is used when it is available from renewables and particularly cost-effective. By 2030, our goal is to transition 1.5 million households to renewable energies. Over 3,000 people are working towards this every day, at more than 80 locations worldwide, from Finland to Australia. Want to take responsibility and build solutions that truly matter? Apply now and help us shape the energy world of tomorrow . Become a part of our mission and learn more about our Product & Tech team! Deine Position We are looking for a Senior Software Engineer - Energy Markets to drive the technical direction of our Energy Markets workstream, with the potential to grow into a lead role. Key responsibilities include: Build and optimize backend services for VPP operations and energy market integrations Design systems at the intersection of backend and data processing pipelines Drive technical decisions and guide fellow engineers on architectural choices Navigate between data engineering, backend engineering, and energy market domains Collaborate with product managers, data engineers, and data scientists across team boundaries Dein Profil The successful candidate will have: Proven experience developing scalable backend solutions with TypeScript Data engineering fundamentals — designing systems bridging backend and data processing Hands-on experience with energy service interfaces (smart meters, optimization, load balancing) Strong knowledge of architectural pat

P-273 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world. Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way. The impact you will have: You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications Collaborate with your fellow Solutions Architects, using your skills to support each other and our users Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community. What we look for: 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role Experience building distributed data systems Comfortable programming in, and debugging, Python and SQL Have built solutions with public cloud providers such as AWS, Azure, or GCP Expertise in one of the following: Data Engineering technologies ( Ex: Spark, Hadoop, Kafka ) Data Science and Machine Learning technologies ( Ex: pandas, scikit-learn, pytorch, Tensorflow ) Avai

Job Requisition ID # 26WD101494 Machine Learning Operations Developer, Inference, AI/ML Platform L'affichage de poste en français suivra / The French job posting follows Position Overview Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking an MLOps Developer to join our AI/ML Platform team. This role will contribute to ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML platform used in the development of machine learning and generative AI solutions powering Autodesk’s suite of products and services. You will collaborate with research and product engineering teams from various domains including design, construction, manufacturing, and media & entertainment to support platform operations. The role is hybrid Toronto or Montreal. Responsibilities Contribute to the operational excellence of our AI/ML Platform by implementing and optimizing MLOps practices Develop and maintain automated deployment pipelines for machine learning models, supporting seamless transitions from development to production Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processing <li style="color:#1d

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have work

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role Synthesia Roleplay Sessions is a training tool that lets people practice real conversations with AI avatars. Instead of just watching training videos, learners do interactive roleplay exercises, like practicing a sales pitch or handling a customer complaint with an AI coach. The AI gives instant feedback so people know what they did well and what to improve. Managers can use a dashboard to track which employees have completed their training, see how well they performed, and measure if the training actually improved their skills. The whole platform is built around learning by doing rather than just passive video watching. For your ML engineer role, you'd be building the AI engine that makes the coaching work. That means creating the models that listen to what learners say during roleplay, score their performance, generate helpful feedback in real time, and decide how the AI avatar should respond next based on what the learner does. This is an applied ML position, not a research one . We expect you to have a good understanding of ML but on the other side to be a good product-focused software developer as you will be expected to work on different products. Please bring with you: Ability to apply your

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. Design systems to speed up the time from idea to deployment of new models. Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. Develop pipelines and automated processes to train and evaluate models in offline and online environments. Integrate ML models into production systems and ensure their scalability and reliability. Collaborate with product and strategy partners to propose, prioritize, and implement new product features. Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production. Must have two (2) years of experience in each of the following: ML algorithms and model architectures; Designing, training and evaluating machine learning models; Productionizing and deploying machine learning models at scale; Orchestrating data pipelines and leveraging large-s

Machine Learning Engineer – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like A

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper