Senior AI Python Engineer – Life Sciences Domain

Job description

EPAM is looking for an experienced Senior AI Python Engineer to join our Life Sciences and Healthcare projects, with a strong focus on bioinformatics and data-driven solutions.

This role is ideal for engineers who want to apply Python, AI, and advanced analytics to real-world biological and biomedical challenges.

You will contribute to impactful projects for global pharmaceutical, biotech, and healthcare companies, supporting solutions in bioinformatics, computational biology, genomics, and AI-driven drug discovery. In this role, you will participate in designing and implementing scalable, cloud-native platforms that process biomedical data, support research and drug development, and enable data-driven decision-making in regulated environments.

Responsibilities

- Contribute to creating cloud-native, AI-driven solutions for Life Sciences using Python

- Assist with building and optimizing data processing pipelines for large-scale biological and biomedical datasets (genomics, transcriptomics, proteomics, clinical data)

- Support the integration and application of Generative AI solutions, including LLMs and RAG, in bioinformatics and drug discovery workflows

- Utilize computational and statistical techniques for high-throughput biological data, including sequence-based and omics data

- Collaborate with bioinformaticians, computational biologists, data scientists, and domain experts to implement technical solutions based on scientific requirements

- Facilitate technical improvements, review code, and ensure high-quality documentation and maintainability

- Enhance AI components within client solutions and EPAM in-house platforms while following best practices for development processes

- Tackle challenges around data scale, security, and performance in computational life sciences applications

- Keep informed about advancements in Life Sciences, AI, and cloud technologies, applying new approaches in projects

Requirements

- 3+ years of experience in Python software engineering, along with practical exposure to Life Sciences, Healthcare, Bioinformatics, Computational Biology, or related domains

- Proficiency in Python and modern web/API frameworks (Django, Flask, FastAPI)

- Experience with scientific and analytical Python libraries (NumPy, Pandas, SciPy, scikit-learn) and/or a relevant M. Sc. or Ph. D. in Bioinformatics, Computational Biology, or a related quantitative field

- Exposure to handling biological, biomedical, or clinical data, including NGS, transcriptomics, proteomics, multi-omics, or genomic data formats (FASTQ, BAM, VCF)

- Familiarity with integrating AI / ML models into production systems in data-intensive or regulated contexts

- Strong understanding of software design principles, data structures, and algorithms

- Hands-on experience with cloud platforms (AWS, Azure, or GCP)

- Strong analytical and problem-solving skills, with the ability to contribute to technical discussions and solution design

- Excellent communication skills and experience working in cross-functional, international teams

- Fluency in English (both written and spoken) at a minimum B2 level