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 include 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 acts like an experienced agent?
Are you motivated to create products that truly make a difference—making the world healthier, safer, and cleaner every day?
If so, we’d love to discuss the innovative products we’re developing.
You will have the opportunity to work on complex, data-intensive challenges in the omics science domains, leveraging ground-breaking research in AI to develop novel algorithms and techniques in this 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.
Collaboration with multi-functional teams to integrate AI/ML solutions into products and services is essential.
This role offers hands-on experience with modern AI technology.
Join us in the genomics revolution!
Responsibilities
Design and develop robust deep learning models for genomics, image processing, time-series analysis, and related 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 considering data variability, noise, and computational efficiency.
Collaborate with multi-functional teams to deploy scalable AI solutions and integrate 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 Science, Mathematics, Statistics, or 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 ML infrastructure (model deployment, 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 with ML models for genomics data analysis.
Experience with containerization and orchestration tools (Docker, Kubernetes).
Expertise in Python; experience with C++/Java is a plus.
Knowledge of MLOps practices and tools.
Familiarity with LLMs, LangChain, LlamaIndex, and RAG frameworks.
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