(Senior) Machine Learning Engineer

📋 Description

• Architect and implement scalable ML systems that integrate multi-modal omics data.
• Develop and deploy graph-based, transformer-based, and generative models including LLMs.
• Build a multi-agent causal AI framework with causal graph learning and knowledge graphs.
• Collaborate with data engineering to design pipelines for large-scale omics data.
• Implement, evaluate, and optimize causal inference methods (DAGs, treatment effects).
• Partner with experimental scientists to ensure outputs are interpretable and testable.

🎯 Requirements

• Ph.D. or M.S. in CS, Physics, Computational Biology, Biostatistics, or related field with 3+ years.
• Proven ML model development experience with transformers, graph nets, generative or causal inference.
• Python and ML frameworks such as PyTorch, TensorFlow, JAX, or PyTorch Geometric.
• Experience with multi-omics or high-dimensional biological data preferred.
• Strong background in probabilistic modeling, causal reasoning, or statistical inference.
• Demonstrated ability to work in cross-disciplinary teams and deliver results in fast-moving environments.

🎁 Benefits

• Healthcare coverage
• Annual incentive program
• Retirement benefits
• Broad range of other benefits