176 to 181 of 181 Remote Amazon SageMaker Jobs

a good understanding of AWS and Azure architecture. There is also an opportunity to get involved in ML projects, and experience in this area (and relevant platforms such as Sagemaker or Azure ML) is desirable but not essential for the role. What We Offer Hybrid working - 2 days a week in the office (SP1 3TB). 25 days of More ❯

member, reporting directly to the Head of AI Hands-on from design to deployment, including infra and validation Strong product exposure, weekly feedback loops with care partners Stack includes SageMaker, Vertex, OpenAI APIs, PyTorch Full-time, remote-first (UK/CET), Your Responsibilities: Designing and shipping AI-powered product features using LLMs and symbolic AI Building out scalable infrastructure More ❯

member, reporting directly to the Head of AI Hands-on from design to deployment, including infra and validation Strong product exposure, weekly feedback loops with care partners Stack includes SageMaker, Vertex, OpenAI APIs, PyTorch Full-time, remote-first (UK/CET), Your Responsibilities: Designing and shipping AI-powered product features using LLMs and symbolic AI Building out scalable infrastructure More ❯

skills Experience with NestJS Advanced proficiency in GraphQL Deep experience with AWS Typescript CDK Familiarity with NoSQL/Document DBs (e.g. DynamoDB, MongoDB) Exposure to AWS Glue, DMS, or SageMaker Expertise in e2e and test automation frameworks Perks and benefits We offer a competitive salary package including: Equity through stock options MacBook + £500 office setup budget 29 days More ❯

Experience with using Python to manipulate data and as a tool for analysis (for example using Pandas). Desirable but not essential: Experience using cloud platforms such as GIT, SageMaker or Data Bricks. KNOWLEDGE: What You know Academic Qualifications: Degree in numerate/statistical subject, or equivalent experience in a related field. Technical Qualifications: No formal required however qualifications More ❯

user needs and deliver measurable improvements. Build and Maintain AI Infrastructure: Architect and manage robust AI infrastructure, integrating models into our platform and ensuring seamless data flow using AWS SageMaker/Vertex AI. Evaluate Emerging Technologies: Research and implement cutting-edge AI tech, including generative AI and reinforcement learning, to enhance platform capabilities. Build Evaluation and Testing Frameworks: Collaborate More ❯