Junior AI Bioinformatics Engineer

Amaris Consulting is seeking a Junior AI Bioinformatics Engineer to support the research and development of generative AI solutions applied to bioinformatics. The role involves building and optimizing AI-driven workflows while collaborating with multidisciplinary teams to enhance biomedical data analysis.

Responsibilities

• Conduct literature reviews on the latest advancements in generative AI, agentic AI, and their applications in healthcare and bioinformatics
• Support the design, development, and evaluation of AI/ML models for biological data workflows (e.g., NGS, precision medicine)
• Implement algorithms and workflows using Python and relevant machine learning frameworks
• Develop and execute benchmarking strategies to assess model performance, robustness, and accuracy
• Contribute to the improvement and optimization of models and workflows
• Ensure reproducibility through proper testing, documentation, and version control practices
• Prepare clear and concise technical documentation, reports, and summaries
• Collaborate with cross-functional teams including data scientists, engineers, and domain experts
• Assist in establishing scalable and reproducible development environments

Skills

• Currently enrolled in or recently completed a Master's degree or PhD in a quantitative field (e.g., Computer Science, Mathematics, Physics, Bioinformatics, or related)
• Strong Python programming skills
• Experience working in Unix/Linux environments, including remote or high-performance computing (HPC) systems
• Hands-on experience in machine learning and deep learning, using frameworks such as PyTorch or similar
• Understanding of model evaluation, validation, and benchmarking techniques
• Strong analytical and problem-solving abilities
• Ability to communicate complex technical concepts clearly
• Collaborative mindset and ability to work in multidisciplinary teams
• Attention to detail and commitment to high-quality deliverables
• Background in statistics, probability, and linear algebra
• Familiarity with generative AI, large language models (LLMs), or agentic AI approaches
• Knowledge of bioinformatics, biological data analysis, or life sciences
• Experience with NGS data or precision medicine applications

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