Machine Learning Data Scientist

Machine Learning Data Scientist (contract) Location: Remote Pay Rate: $80-$90 Hourly (DoE) Role Overview As a Machine Learning Data Scientist, you will collaborate closely with researchers, engineers, designers, and product partners to evaluate emerging AI technologies, build rapid prototypes, and develop novel machine learning solutions that make advanced research understandable, usable, and testable. You will design experiments, create evaluation frameworks, fine-tune and validate models, and help identify which technologies warrant broader investment and adoption. This role is ideal for a technically strong builder who enjoys ambiguity, learns quickly, and can move fluidly between research papers, datasets, prototypes, and production-scale systems. Success requires scientific rigor, strong product judgment, and a passion for turning breakthrough ideas into tools, workflows, and experiences that empower researchers, developers, and customers. This role is ideal for a technically strong builder who enjoys ambiguity, learns quickly, and can move fluidly between research papers, datasets, prototypes, and production-scale systems. Success requires scientific rigor, strong product judgment, and a passion for turning breakthrough ideas into tools, workflows, and experiences that empower researchers, developers, and customers. Candidates should be prepared to discuss projects that demonstrate the ability to translate research, emerging technology, or novel ideas into working prototypes, experiments, or deployed solutions. Job Responsibilities Fine-tune and improve a variety of sophisticated software implementation projects Gather and analyze system requirements, document specifications, and develop software solutions to meet client needs and data Analyze and review enhancement requests and specifications Implement system software and customize to client requirements Prepare the detailed software specifications and test plans Code new programs to client's specifications and create test data for testing Modify existing programs to new standards and conduct unit testing of developed programs Create migration packages for system testing, user testing, and implementation Provide quality assurance reviews Perform post-implementation validation of software and resolve any bugs found during testing Additional Responsibilities Collaborate with Microsoft Research teams to evaluate, adapt, and operationalize emerging AI and machine learning innovations into functional prototypes and experimental systems. Design and execute quantitative and qualitative experiments that measure model performance, user engagement, research impact, and technology adoption. Develop evaluation frameworks, benchmarks, and success metrics for foundation models, generative AI systems, multimodal experiences, and agent-based workflows. Fine-tune, validate, and benchmark machine learning models using real-world datasets and emerging research techniques. Build rapid prototypes and proof-of-concepts that help researchers, partners, and stakeholders assess the practical value of new technologies. Stay current with advances in machine learning, generative AI, agentic systems, multimodal models, and evaluation methodologies, identifying opportunities to apply new capabilities across Microsoft Research. Required Qualifications Education: Bachelor's degree in computer science, computer engineering, or a related technical field is required. Experience: 5-7 years of experience is required. Candidates must be available for at least a 12-month assignment. Technical Skills: Strong foundations in software engineering, machine learning, statistics, and experimental design. Experience building data-intensive applications, machine learning systems, or AI-powered products. Experience evaluating, debugging, and improving machine learning models and data pipelines. Proficiency in programming with experience in problem diagnosis and resolution. Ability to thrive in ambiguous, rapidly changing environments. Preferred Qualifications Availability for an 18-month assignment. Demonstrated ability to rapidly learn new projects and deliver results quickly. Hands-on experience with AI-assisted coding and rapid prototyping. Experience with foundation models, generative AI systems, multimodal models, agentic workflows, or retrieval-augmented generation (RAG).