AI Engineer

Thermo Fisher Scientific is a leader in clinical trial services, and they are seeking a highly motivated AI Engineer to advance their digital strategy. This role involves designing, building, deploying, and optimizing AI solutions to enhance clinical research and development operations.

Responsibilities:

• Design, develop, and deploy machine learning and generative AI models to support CRG Digital priorities including predictive analytics, text/NLP solutions, automation, and intelligent decision support
• Apply statistics, programming, data modeling, simulation, and advanced mathematics to business problems
• Evaluate and optimize model performance using appropriate validation metrics and techniques
• Build reusable model pipelines, APIs, and components for scalable AI product deployment
• Preprocess, clean, transform, and integrate structured and unstructured datasets from clinical and operational sources
• Build and maintain ETL/data workflows that support ML and generative AI workloads
• Work with relational, document, columnar, graph, and object store systems; design schemas for AI and analytics use cases
• Ensure data quality, reproducibility, lineage, and governance compliance
• Collaborate with software engineering and platform teams to integrate AI models into production systems with appropriate monitoring and observability
• Support documentation, traceability, and regulatory readiness (e.g., auditability, GxP considerations)
• Contribute to CRG Digital’s product development lifecycle including discovery, prototyping, testing, deployment, and iteration
• Stay current on emerging AI and ML technologies, evaluating opportunities for CRG Digital roadmaps
• Contribute to an innovative ecosystem involving external partners and technology collaborators
• Support internal digital and AI upskilling through documentation, best practices, and knowledge sharing

Requirements:

• Bachelor's degree or equivalent and relevant formal academic/vocational qualification
• Previous experience in machine learning, AI model development, or data science that provides the knowledge, skills, and abilities to perform the job (comparable to 2+ years)
• Proficiency in modern SQL, Python, Spark, and associated AI/ML packages
• Experience with generative AI, large language models, NLP, prompt engineering, and LLMOps best practices
• Strong exploratory data analysis skills: ability to validate, visualize, and communicate model behavior
• Experience with cloud architecture, distributed computing, and modern ML platforms
• Familiarity with data governance, data security, and compliance requirements (preferably in a regulated or clinical environment)
• Ability to manage multiple priorities in a matrixed environment
• Excellent analytical thinking, problem-solving, and communication skills
• Ability to work independently with minimal supervision and collaborate effectively with cross-functional teams
• Able to communicate, receive, and understand information and ideas with diverse groups of people in a comprehensible and reasonable manner
• Able to work upright and stationary for typical working hours
• Ability to use and learn standard office equipment and technology with proficiency
• Able to perform successfully under pressure while prioritizing and handling multiple projects or activities
• Must be legally authorized to work in the United States/Mexico without sponsorship
• Must be able to pass a comprehensive background check, which includes a drug screening (US)
• Master's degree preferred
• Experience with exploratory data analysis techniques, machine learning algorithms (including generative models), model validation techniques, and data visualization techniques
• Experience with relational, document, columnar, graph, and object store systems; design schemas for AI and analytics use cases
• Support documentation, traceability, and regulatory readiness (e.g., auditability, GxP considerations)
• Stay current on emerging AI and ML technologies, evaluating opportunities for CRG Digital roadmaps
• Contribute to an innovative ecosystem involving external partners and technology collaborators
• Support internal digital and AI upskilling through documentation, best practices, and knowledge sharing