Senior Engineer I, AI/Data Science

Start free →

Or apply yourself on the official page →

About the role

At Element Biosciences, we are passionate about our mission to empower the scientific community with more freedom and flexibility to accelerate our collective impact on humanity. We have built a highly efficient product-driven organization where employees can learn, grow, and thrive in a challenging but encouraging environment. We are committed to scientific integrity, collegiality, honesty, objectivity, and openness. We are seeking a highly skilled and motivated Senior Engineer, AI/Data Science to join our dynamic team. The ideal candidate will have experience in data science and machine learning, with a background in working with multiomic and single-cell data and/or image processing and computer vision. This role involves creating, exploring, and analyzing models, as well as applying image processing techniques to support our research and development efforts and contribute to critical programs. This role will report to Vice President, AI and will be an onsite role at our headquarters in San Diego. If you possess the following and want to make a meaningful impact, we invite you to explore this role. Essential Functions and Responsibilities: • Develop and implement deep learning models (CNNs, Vision Transformers, U-Net variants, and related architectures) for biological image analysis and classification, under the guidance of senior team members • Support deployment and maintenance of neural network models on cloud infrastructure (e.g., AWS) or directly on imaging instruments • Apply image processing and computer vision techniques to analyze multimodal biological images, including segmentation, feature extraction, and quality scoring • Contribute to end-to-end ML pipelines — from data ingestion and preprocessing through model training, validation, and inference • Analyze and interpret single-cell and multiomic data to support biological context and downstream interpretation of imaging results • Collaborate with cross-functional teams including biology, software engineering, and instrumentation to support experiment design and translate biological requirements into modeling objectives • Explore and analyze imaging datasets to identify patterns, failure modes, and opportunities for model improvement • Communicate findings and model performance metrics to stakeholders through reports and presentations • Partner with molecular biology, chemistry, and data-engineering teams to validate findings • Stay current with the latest advancements in deep learning, computer vision, and computational biology, and evaluate their applicability to internal research problems Education and Experience: • PhD with 0–3 years of experience is strongly preferred or a minimum of Master’s degree in Computer Science, Electrical Engineering, Bioinformatics, Computational Biology, or a related field with 2–4 years of relevant experience • Experience developing deep learning models for image analysis is required; exposure to production or deployment environments (cloud-hosted or on-instrument) is a plus • Proficiency with deep learning architectures including CNNs, Vision Transformers (ViT), U-Net, or attention-based models • Experience with biological or biomedical image modalities (e.g., fluorescence microscopy, brightfield, high-content imaging) is a plus • Proficiency in Python and relevant deep learning and data science libraries: PyTorch, torchvision, OpenCV, Scikit-learn, NumPy, Pandas, and related tools • Familiarity with cloud computing platforms (e.g., AWS) is a plus • Proficiency in working with multiomic and single-cell data is a plus • Familiarity with bioinformatics and computational biology tools and databases is a plus • Knowledge of experimental design and statistical analysis • Strong background in statistics and comfor

View the official posting →