From Element Biosciences's posting. “We” and “our” refer to the employer.
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, Machine Learning 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 advanced image processing techniques to drive 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:
Design, develop, and optimize deep learning models (CNNs, Vision Transformers, U-Net variants, and related architectures) for biological image analysis and classification
Deploy and maintain production-grade neural network models on cloud infrastructure (e.g., AWS) or directly on imaging instruments, ensuring reliability, scalability, and performance
Apply advanced image processing and computer vision techniques to analyze multimodal biological images, including segmentation, feature extraction, and quality scoring
Develop and manage 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 co-design experiments and translate biological requirements into modeling objectives
Explore and analyze large-scale imaging datasets to identify patterns, failure modes, and opportunities for model improvement
Communicate findings, model performance metrics, and technical trade-offs to stakeholders through reports and presentations
Stay current with the latest advances in deep learning, computer vision, and computational biology, and evaluate their applicability to internal research problems
Education and Experience:
Master's degree in Computer Science, Electrical Engineering, Bioinformatics, Computational Biology, or a related field with 5–7 years of relevant experience, or PhD with 0–3 years of experience
Hands-on experience developing and deploying deep learning models for image analysis in production environments — either cloud-hosted or on-instrument — is required
Strong proficiency with modern deep learning architectures including CNNs, Vision Transformers (ViT), U-Net, and attention-based models; familiarity with self-supervised or contrastive learning methods is a plus
Experience with biological or biomedical image modalities (e.g., fluorescence microscopy, brightfield, high-content imaging) is strongly preferred
Proficiency in Python and relevant deep learning and data science libraries: PyTorch, torchvision, OpenCV, Scikit-learn, NumPy, Pandas, and related tools
Experience with cloud computing platforms (e.g., AWS), including model serving, containerization (Docker), and GPU-accelerated compute
Familiarity with model calibration, uncertainty quantification, or performance evaluation frameworks is a plus
Experience with single-cell or multiomic data analysis tools and workflows is a plus
(not required)
Knowledge of experimental design and statistical analysis
Strong background in statistics and comfort reasoning about model outputs quantitatively
Excellent problem-solving skills, attention to detail, and ability to work across scientific and engineering disciplines
Physical Requirements:
Frequently moves boxes weighing up to 20 pounds
Location:
San Diego – on-site
Travel:
Domestic travel up to 10%
Job Type:
Full-time/Exempt
Base Compensation Pay Range:
$139,000 - $183,000
In addition to base compensation noted above, you will be eligible for stock options, discretionary annual bonus, no cost health insurance plans, 401k with company match, and flexible paid time off.
Please note: Base compensation will depend on multiple factors, including geographic location, qualifications, and experience.
We foster an environment such that all people are afforded the freedom to pursue their passions without regard to race, color, religion, national or ethnic origin, gender (including pregnancy), sexual orientation, gender identity or expression, age, disability, veteran status or any other characteristics protected by law.
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