Staff AI Developer

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

As part of the Thermo Fisher Scientific team, youâll 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 worldâs toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.

DESCRIPTION:
Join our AI team where you'll design and implement artificial intelligence solutions that help make the world healthier, cleaner, and safer. As a Staff Engineer in Artificial Intelligence, you'll architect and develop advanced AI/ML solutions that drive innovation across our diverse business units. You'll collaborate with data scientists, researchers, and business stakeholders to create scalable AI architectures, optimize model performance, and implement state-of-the-art machine learning solutions. This role includes developing predictive models for patient and donor risk, working with healthcare datasets, and integrating AI capabilities into applications, often leveraging cloud-based platforms.

Key ResponsibilitiesÂ

• Design, develop, and deploy AI/ML models and algorithmsÂ

• Build predictive models for patient and donor risk assessment (e.g., eligibility, adverse outcomes, fraud/risk scoring)Â

• Work with structured and unstructured healthcare/life sciences data (EHR, clinical, donor data)Â

• Perform data preprocessing, feature engineering, and model evaluationÂ

• Integrate AI models into production systems via APIs or microservicesÂ

• Collaborate with data scientists, clinicians, and business stakeholdersÂ

• Optimize model performance, accuracy, and interpretabilityÂ

• Utilize cloud AI/ML platforms (AWS, Azure, Google Cloud)Â

• Monitor, retrain, and maintain models in production (MLOps practices)Â

• Ensure compliance with healthcare regulations (HIPAA, FDA, GDPR as applicable)Â

• Apply ethical AI practices, including bias detection and model transparencyÂ

• Stay updated with advancements in AI, healthcare analytics, and risk modelingÂ

Required QualificationsÂ

• Bachelorâs or Masterâs degree in computer science, AI, Data Science, or related fieldÂ

• 5+ years of experience in AI/ML developmentÂ

• Strong programming skills in Python (preferred), C#.Net OR Java, or C++Â

• Experience with machine learning frameworks:Â TensorFlow ORÂ PyTorch OR Scikit-learnÂ

• Experience developing risk models (classification, regression, survival analysis)Â

• Familiarity with Natural language processing (NLP) frameworkÂ

• Knowledge of healthcare or life sciences data, including patient and donor datasetsÂ

• Experience with data preprocessing and analysis (Pandas, NumPy)Â

• Familiarity with REST APIs and software development practicesÂ

• Understanding of statistics, probability, and data structuresÂ

• Experience with version control (GitHub)Â

• Strong problem-solving and analytical skillsÂ

• Good communication and collaboration abilitiesÂ

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Preferred QualificationsÂ

â¯â¯â¯â¢â¯â¯â¯Experience with Generative AI and large language models (LLMs)Â

â¯â¯â¯â¢â¯â¯â¯Familiarity with healthcare data standards (HL7, FHIR)Â

â¯â¯â¯â¢â¯â¯â¯Experience with cloud AI services:Â

â¯â¯â¯â¯â¯â¯â¢â¯â¯â¯AWS SageMakerÂ

â¯â¯â¯â¯â¯â¯â¢â¯â¯â¯Azure AI / ML StudioÂ

â¯â¯â¯â¯â¯â¯â¢â¯â¯â¯Google Vertex AIÂ

â¯â¯â¯â¢â¯â¯â¯Knowledge of MLOps tools (MLflow, Kubeflow, Docker, Kubernetes)Â

â¯â¯â¯â¢â¯â¯â¯Experience with big data tools (Spark, Kafka)Â

â¯â¯â¯â¢â¯â¯â¯Background in clinical analytics, epidemiology, or biostatisticsÂ

â¯â¯â¯â¢â¯â¯â¯AI or cloud certificationsÂ