Machine Millwright Titleist Jobs

Engineer 6, Machine Learning, Data & AI — 5 Locations. Apply via Workday.

About Anyscale At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the role The Customer Engineer will play a crucial role in the customers’ post-sale journey - helping them to onboard, adopt and grow on Anyscale, troubleshooting and resolving open customer tickets and driving consumption. Anyscale is an ever evolving platform and hence will require close co-ordination with our engineering teams to debug complex issues. This is an exciting role for those who are technically curious and passionate about ML/AI, LLM, vLLM and the role of AI in next generation applications. It’s an opportunity to make a significant impact in a collaborative, fast-paced environment while building a new segment in this space. In this role, you’ll be able to Resolve customer issues and help in their successful adoption of Anyscale platform Be a technical advisor, and internal champion for our key customers Own customer issues end-to-end, from troubleshooting, triaging, escalations and eventual resolution Participate in our follow-the-sun customer support model to ensure continuity in resolving high priority tickets Keep track of open customer bugs and feature requests to influence prioritization and provide timely customer updates upon resolution Contribute towards improvement of internal tools an

Machine Operator II - 3rd Shift - $21.90 + $1.50 Shift Premium — Kalamazoo, Michigan. Apply via Workday.

Machine Operator / Integrator — Kiryat-Gat, South District, Israel. Apply via Workday.

Machine Learning Data Engineer (AIM2) — United States - Massachusetts - Cambridge. Apply via Workday.

Principal Machine Learning Engineer — 3 Locations. Apply via Workday.

Senior Machine Learning Engineer, Perception - Autonomous Driving — 3 Locations. Apply via Workday.

Senior Machine Learning Engineer 5 — 2 Locations. Apply via Workday.

Principal Machine Learning Engineer, Agent Harness - Meta Factory — San Jose. Apply via Workday.

Machine Learning Engineer — San Francisco. Apply via Workday.

Machine Learning Engineer — Noida. Apply via Workday.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Ship state of the art models to production. Design and implement novel research ideas. Build elegant training/deployment pipelines. Join us at a pivotal moment, shape what we build and wear multiple hats as an intern! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term. As a Machine Learning Intern, you will: Design, train and improve upon cutting-edge models. Help us develop new techniques to train and serve models safer, better, and faster. Train extremely large-scale models on massive datasets. Explore continual and active learning strategies for streaming data. Learn from experienced senior machine learning technical staff. Work c

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. This position may be a hybrid or fully remote position, as decided by your manager. If designated as hybrid, you’ll divide your time between working remotely from your home and an office location, so you should live within commuting distance. If designated as remote, you’ll be working remotely from your home and may occasionally visit a GoDaddy office to meet with your team for events or meetings. Your hiring manager can share more about this role’s hybrid or remote designation. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. GoDaddy is not currently considering candidates for this role in California, Seattle, or NYC. Join our team... Join GoDaddy's Applied AI and Machine Learning team, where you'll help shape the future of how millions of small business owners leverage AI to grow and run their businesses. Our team develops machine learning models and generative AI solutions that directly influence revenue, customer experience, personalization, pricing, and business outcomes at scale. As a Staff Machine Learning Scientist, you'll operate with a high degree of autonomy, partner closely with engineers and product leaders, and drive innovative AI initiatives from concept to production in a fast-moving environment that values purposeful action and measurable impact. What you'll get to do... Lead the development and deployment of machine learning and generative AI

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

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