Payrate: $90.00- $95.00/hr. Summary: 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 client 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.
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 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
Collaborate with 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 Research.
Qualifications:
Bachelor's degree in technical field such as computer science, computer engineering or related field required
5-7 years' experience required
Strong technical foundations in software engineering, machine learning, statistics, and experimental design.
Experience building data-intensive applications, machine learning systems, experimentation platforms, or AI-powered products.
Experience evaluating, debugging, and improving machine learning models, data pipelines, and AI-powered applications.
Experience in programming and experience with problem diagnosis and resolution
Ability to thrive in ambiguous, rapidly changing environments where requirements evolve through experimentation and discovery.
Experience with foundation models, generative AI systems, multimodal models, agentic workflows, retrieval-augmented generation (RAG), or related AI technologies.
Pay Transparency: The typical base pay for this role across the U.S. is: $90.00- $95.00/hour. Non-exempt positions are eligible for overtime at a rate of 1.5 times the base hourly rate for all hours worked in excess of 40 in a work week, or as required by state or local law. Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education and experience. Full-time employees are eligible to select from different benefits packages. Packages may include medical, dental, lifeion benefits, health savings accounts with qualified medical plan enrollment, 10 paid days off, 3 days paid bereavement leave, 401(k) plan participation with employer match, life and disability insurance, commuter benefits, dependent care flexible spending account, accident insurance, critical illness insurance, hospital indemnity insurance, accommodations and reimbursement for work travel, and discretionary performance or recognition bonus. Sick leave and mobile phone reimbursement provided based on state or local law.