Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue exceeding $40 billion and extensive investment in R&D. Our Mission is to enable our customers to make the world healthier, cleaner and safer. The customers we serve fall within pharmaceutical and biotech companies, hospitals and clinical diagnostic labs, universities, research institutions and government agencies. Our innovations drive scientific breakthroughs, from pioneering research to routine testing and real-world applications.
Summary of Opportunity
Do you thrive on building systems that push the boundaries of AI and GenAI? Are you driven to address complex, real-world challenges with dynamic software that service like an experienced agent? Are you driven to create products that truly make a difference – making the world heathier, safer, cleaner every day? If so, we’d love to discuss the innovative products we’re developing. You'll have the opportunity to immerse yourself in complex, data-intensive challenges in the omics science domains. You'll have the opportunity to use ground breaking research in AI to develop novel algorithms and techniques in this unique, compelling, growing industry.
We are seeking a mid-career developer with a strong interest and background in AI and generative AI technologies. You will work with deep learning models, optimize algorithm performance, and drive innovation with AI-powered solutions. You will collaborate with multi-functional teams to integrate AI/ML solutions into products and services. This role offers hands-on experience with modern AI technology. Join us in and be a part of the genomics revolution!
Responsibilities
- Design and develop robust deep learning models for use in genomics, image processing, time-series analysis and genomics-adjacent applications.
- Develop and implement data processing pipelines for large-scale genomics datasets (e.g., sequencing data, variant calling data, gene expression data).
- Optimize model performance for real-world scenarios, considering factors like data variability, noise, and computational efficiency.
- Collaborate with multi-functional teams to deploy scalable AI solutions and integrate AI models into customer-facing applications.
- Implement automated testing and monitoring systems to assess model quality and performance.
- Deploy and maintain ML models in production environments, ensuring scalability and reliability.
- Present technical findings and progress updates to team members and partners.
Education
BS in Computer Sciences, Mathematics, Statistics or a related field; a Master’s degree is highly preferred
Required Qualifications
- 3+ years of experience in developing and deploying machine learning models.
- Proficient in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with data preprocessing and feature engineering techniques.
- Experience with basic ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- Familiarity with version control systems like Git.
Desired Qualifications
- Master's or Ph.D. in a relevant field.
- 5+ years of experience in developing and deploying machine learning models for genomics data analysis.
- Experience with containerization and orchestration tools (Docker, Kubernetes).
- Expert in Python. Experience with C++/ Java is a plus.
- Experience with MLOps practices and tools.
- Knowledge of LLMs, LangChain, LlamaIndex, and RAG frameworks.
