AI Engineer

Thermo Fisher Scientific seeks an AI Engineer (Scientist II, Data Sciences) to design, build, deploy, and optimize AI models and generative AI solutions that advance CRG Digital priorities. This remote role is based in North Carolina and involves close collaboration with data scientists, software engineers, and domain experts to translate business needs into scalable AI products.

Responsibilities

• Design, implement, and deploy machine learning and generative AI models to support CRG Digital priorities, including predictive analytics, NLP/text solutions, automation, and intelligent decision support.
• Apply statistical methods, programming, data modeling, simulations, and advanced mathematics to address business problems.
• Assess and optimize model performance using appropriate validation metrics and evaluation techniques.
• Develop reusable model pipelines, APIs, and components to enable scalable AI product deployment.
• Preprocess, clean, transform, and integrate both structured and unstructured datasets from clinical and operational sources.
• Build and maintain ETL and data workflows that support ML and generative AI workloads.
• Collaborate with teams across relational, document, columnar, graph, and object store systems; design schemas for AI and analytics use cases.
• Ensure data quality, reproducibility, lineage, and governance compliance.
• Partner with software engineering and platform teams to integrate AI models into production systems with monitoring and observability.
• Support documentation, traceability, and regulatory readiness including auditability and GxP considerations.
• Contribute to the CRG Digital product lifecycle from discovery and prototyping through testing, deployment, and iterative improvement.
• Stay informed on emerging AI and ML technologies and evaluate opportunities to feed CRG Digital roadmaps.
• Support an innovative ecosystem by engaging with external partners and technology collaborators.
• Foster internal digital and AI upskilling through documentation, best practices, and knowledge sharing.

Requirements

• Bachelor's degree or equivalent; Master's degree preferred. Equivalency of education, training, and related experience may be considered.
• Minimum of 2 years of experience in machine learning, AI model development, or data science.
• Proficiency with SQL, Python, Spark, and common AI/ML libraries and packages.
• Experience with generative AI, large language models, NLP, prompt engineering, and LLMOps best practices.
• Strong exploratory data analysis skills, including validation, visualization, and clear communication of model behavior.
• Experience with cloud architecture, distributed computing, and modern ML platforms.
• Familiarity with data governance, data security, and regulatory/compliance requirements, preferably in regulated or clinical environments.
• Ability to manage multiple priorities in a matrixed organization.
• Excellent analytical thinking, problem-solving, and communication abilities.
• Ability to work independently with minimal supervision and collaborate effectively with cross-functional teams.
• Authorized to work in the United States or Mexico without sponsorship.
• Ability to pass a comprehensive background check including drug screening.
• Effective communication across diverse groups in a clear and reasonable manner.
• Ability to sit or stand as required during typical working hours.
• Proficiency with standard office equipment and technology.
• Ability to work under pressure while prioritizing multiple projects or activities.
• Occasional travel may be required (up to 20%).

Technologies

• Python, SQL, Spark
• TensorFlow, PyTorch, Keras, scikit-learn
• LangChain/LangGraph, OpenAI/LLM SDKs
• Pandas, NumPy, Jupyter
• Databricks, AWS, Azure, GCP
• S3, Azure Blob Storage
• Git/GitHub

Benefits

• Eligible for a variable annual bonus