Staff Engineer, AI/ML Algorithms Operations

• 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

• BSin Computer Sciences, Mathematics, Statistics ora relatedfield;a Master's degreeis highlypreferred

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.