Staff/Senior Artificial Intelligence Application Engineer

Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job 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%