About this Data Engineering Technical Supervisor (Medior) – Databricks & Python role at Thermo Fisher Scientific
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.
DESCRIPTION:
Join us to help shape the future of scientific discovery through artificial intelligence. As an AI Engineer III, you'll develop advanced AI solutions that enable our customers to make breakthrough advances in healthcare, life sciences, and laboratory productivity. Working within our Data & AI group, you'll collaborate across divisions to design, develop, and deploy sophisticated machine learning models and AI applications that solve complex analytical challenges. This role offers the opportunity to work with state-of-the-art AI technologies, including generative AI, natural language processing, and computer vision, while contributing to our mission of making the world healthier, cleaner, and safer.
REQUIREMENTS:
• Advanced Degree plus 3 years of experience, or Bachelor's Degree plus 5 years of experience in AI/ML engineering and development
• Preferred Fields of Study: Computer Science, AI, Data Science, Software Engineering or related field
• Strong programming skills in Python and ML frameworks (TensorFlow, PyTorch)
• Expertise in implementing deep learning, NLP, and computer vision algorithms
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices
• Proficiency in microservices architecture and RESTful API design
• Knowledge of data structures, algorithms, and statistical analysis
• Experience with data preprocessing, feature engineering, and model training
• Hands-on experience deploying ML models using containers (Docker, Kubernetes)
• Experience with generative AI models (LLMs, GANs, VAEs)
• Understanding of AI model testing, validation, and performance optimization
• Familiarity with big data technologies (Spark, Hadoop, Databricks)
• Strong problem-solving and analytical capabilities
• Excellent collaboration and communication abilities
• Experience with agile development methodologies
• Ability to work effectively in cross-functional teams
• Commitment to staying current with AI/ML technological advances
• Travel may be required up to 10%