AI Engineer
$80k - $100kThermo Fisher Scientific
Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description At Thermo Fisher’s PPD clinical research business, we’re using digital innovation, data science, and AI to reimagine how life-changing therapies reach patients. Our teams combine deep scientific expertise with advanced analytics, automation, and digital platforms to make research smarter, faster, and more connected. We know that innovation happens when diverse minds meet. Our Digital Science, Data, and AI professionals collaborate closely with scientists, clinicians, and operational experts to solve real-world challenges in clinical research. Alongside our partnership with Open AI, you can be part of the collaboration that will help to improve the speed and success of drug development, enabling customers to get medicines to patients faster and more cost effectively. Position Summary: We are seeking a highly motivated AI Engineer (known internally as a Scientist II, Data Sciences, band 5) to help design, build, deploy, and optimize AI solutions that advance CRG's digital strategy. In this role, you will design, implement, and optimize AI models that support data analysis, automation, and innovation. You'll collaborate with data scientists, software engineers, and domain experts to translate business needs into scalable, intelligent solutions. The ideal candidate will be proficient in applying statistics, programming, data modeling, simulation, and advanced mathematics to business questions, with a specific focus on Generative AI. Proven experience needed with exploratory data analysis techniques, machine learning algorithms (including generative models), model validation techniques, and data visualization techniques. Strong knowledge in technical areas such as SQL, Python, Spark, Jupyter, and associated packages and libraries, specifically tailored to Generative AI. AI and Machine Learning Development 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. Data Engineering and Data Management 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. Digital Product Integration and Lifecycle Management 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. Innovation, Partnerships, and Enablement 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. Tools, Technologies, and Platforms Programming: Python, SQL, Spark Libraries and Frameworks: TensorFlow, PyTorch, Keras, scikit-learn, LangChain/LangGraph, OpenAI/other LLM SDKs Data Tools: Pandas, NumPy, Jupyter Cloud and Platforms: Databricks, AWS, Azure GCP; S3 or Azure Blob Storage Version Control: Git/GitHub Education and Experience: Bachelor's degree or equivalent and relevant formal academic/vocational qualification. Master's degree preferred. 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). In some cases, an equivalency, consisting of a combination of appropriate education, training, and/or directly related experience, will be considered sufficient for an individual to meet the requirements of the role. Knowledge, Skills, and Abilities: 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. At Thermo Fisher Scientific, we are committed to fostering a healthy and harmonious workplace for our employees. We understand the importance of creating an environment that allows individuals to excel. Please see below for the required qualifications for this position, which also includes the possibility of equivalent experience: 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. May require as-needed travel (0-20%). Location: Remote US- east coast time zone. Relocation assistance is NOT provided.
- Must be legally authorized to work in the United States or Mexico without sponsorship.
- Must be able to pass a comprehensive background check, which includes a drug screening.
$50.5k - $112.5k
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