Senior Machine Learning Engineer

Responsibilities

• Design, develop, and optimize deep learning models (CNNs, Vision Transformers, U-Net) for biological image analysis
• Deploy and maintain production-grade neural network models on cloud infrastructure (AWS) or imaging instruments
• Apply advanced image processing and computer vision techniques for segmentation, feature extraction, and quality scoring
• Develop and manage end-to-end ML pipelines from data ingestion to inference
• Analyze single-cell and multiomic data to support biological context
• Collaborate with biology, software engineering, and instrumentation teams
• Communicate findings and technical trade-offs to stakeholders

Requirements

• Master's degree in CS, EE, Bioinformatics, or related field with 5–7 years experience, or PhD with 0–3 years experience
• Hands-on experience developing and deploying deep learning models for image analysis in production
• Proficiency in Python and libraries including PyTorch, torchvision, OpenCV, Scikit-learn, NumPy, and Pandas
• Experience with cloud computing (AWS), Docker, and GPU-accelerated compute
• Strong background in statistics and quantitative reasoning

Preferred Qualifications

• Experience with biological or biomedical image modalities (fluorescence microscopy, brightfield)
• Familiarity with self-supervised or contrastive learning methods
• Experience with model calibration or uncertainty quantification
• Experience with single-cell or multiomic data analysis tools

About the Company

Element Biosciences is passionate about empowering the scientific community with more freedom and flexibility to accelerate collective impact on humanity through efficient, product-driven innovation.