Senior Staff AI / ML Solutions Engineer
About The Position
Thermo Fisher Scientific is hiring a Senior Staff AI/ML Solutions Engineer for its Clinical Research Group (CRG) to support the Finance organization. This senior individual contributor will serve as the hands-on technical lead for AI initiatives that improve finance processes, decision-making, and productivity. The role translates business needs into practical AI solutions and leads technical delivery from discovery and architecture through development, evaluation, deployment, and ongoing improvement. The position provides technical direction and responsibility for project outcomes while collaborating across business and technology teams and mentoring junior colleagues. People management may be added as business needs evolve, while hands-on technical leadership remains the primary responsibility. The role is remote in the United States, with preference for candidates in EST or CST. Relocation assistance is not provided. As-needed travel may be required (0–20%). Candidates must be legally authorized to work in the United States without sponsorship and pass a comprehensive background check, including drug screening.
Requirements
- Advanced degree and 6 years of experience in computer science, data science, engineering, or a related technical field and AI; or a bachelor's degree and 8 years of such experience.
- Demonstrated experience serving as technical lead for AI or advanced analytics projects, including delivery into production.
- Strong hands-on proficiency in Python and SQL, with experience building maintainable applications and data integrations.
- Practical experience developing generative AI solutions using platforms such as Azure OpenAI or Amazon Bedrock.
- Experience integrating AI models with enterprise data and applications, including retrieval-augmented generation, APIs, and workflow orchestration.
- Ability to evaluate AI solution quality and explain limitations, technical tradeoffs, and deployment considerations.
- Experience with cloud services and data platforms such as AWS, Azure, Snowflake, or Databricks.
- Working knowledge of data architecture, ETL/ELT processes, data quality, and access controls.
- Experience using version control, testing, CI/CD, and collaborative development tools.
- Strong communication skills and ability to translate business needs into technical requirements and delivery plans.
- Ability to communicate, receive, and understand information and ideas with diverse groups of people in a comprehensible and reasonable manner.
- Ability to work upright and stationary for typical working hours.
- Ability to use and learn standard office equipment and technology with proficiency.
- Ability to perform successfully under pressure while prioritizing and handling multiple projects or activities.
- Must be legally authorized to work in the United States without sponsorship.
- Must be able to pass a comprehensive background check, including a drug screening.
Nice To Haves
- Experience applying AI to processes, analytics, or enterprise productivity.
- Experience with distributed data processing technologies such as PySpark, Apache Spark, and Delta Lake.
- Experience designing and implementing enterprise data models and semantic layers that support consistent business definitions, analytics, and AI applications.
- Experience with predictive modeling and statistical analysis.
- Experience using Azure DevOps or JIRA within Agile delivery teams.
Responsibilities
- Lead technical delivery of AI projects, defining solution architecture, implementation plans, dependencies, and acceptance criteria.
- Partner with finance and other business stakeholders to identify valuable AI use cases, assess feasibility, and establish measurable outcomes.
- Design, build, and integrate AI applications using generative AI, machine learning, enterprise data, and workflow automation as appropriate.
- Develop prototypes and production solutions, selecting technologies based on accuracy, reliability, security, scalability, performance, and cost.
- Establish evaluation approaches for AI outputs, including quality, robustness, and appropriate human review.
- Design and implement data pipelines, APIs, and enterprise integrations needed to support AI solutions.
- Collaborate with IT, architecture, cybersecurity, privacy, and data governance teams to meet applicable requirements throughout development and deployment.
- Apply software engineering practices, including version control, code review, testing, documentation, and automated deployment.
- Define monitoring, support, and operational handoff requirements; investigate issues and improve deployed solutions.
- Communicate technical recommendations, tradeoffs, project risks, and results to technical and business audiences.
- Mentor junior data scientists and engineers through design reviews, code reviews, and collaborative problem-solving.
- Guide technical contributors and coordinate delivery across functions.
Benefits
- Variable annual bonus may be available based on company, team, and/or individual performance results in accordance with company policy.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
