Job Description

We are looking for a talented and driven Machine Learning Engineer to join a high-impact research team focused on advancing machine learning methods for drug development and clinical trial design! This is a unique opportunity to work on highly visible projects that influence real-world healthcare outcomes. You’ll have the chance to publish in leading journals and conferences while contributing to applied science with tangible clinical impact.

Position: Machine Learning Engineer – Clinical Trial Design

Job Type: Contract

Location: Remote (must be available during PST hours) OR onsite preferred (South San Francisco, CA)

About the Role:

We are looking for a talented and driven Machine Learning Engineer to join a high-impact research team focused on advancing machine learning methods for drug development and clinical trial design. This initiative, part of a larger computational sciences organization, explores state-of-the-art techniques such as multimodal generative modeling, representation learning, and reinforcement learning.

Responsibilities:

• Develop and implement deep learning algorithms for medical image analysis, including semantic segmentation and object detection.
• Collaborate with a multidisciplinary team of machine learning researchers, imaging scientists, clinical experts, and decision-makers to integrate AI-driven insights into trial design and disease understanding.
• Analyze large-scale biological and clinical datasets to extract actionable insights for therapeutic development.
• Stay current with cutting-edge developments in machine learning and its healthcare applications.
• Contribute to peer-reviewed publications and conference presentations.

Qualifications:

• Education: M.S. or higher in Computer Science, Machine Learning, Statistics, Mathematics, Physics, Bioinformatics, Bioengineering, or a related quantitative discipline.
• Experience: Demonstrated success in developing and applying advanced machine learning techniques in academic or industry environments.

Technical Skills:

• Strong programming proficiency in Python
• Experience with modern ML frameworks such as JAX, PyTorch, and TensorFlow
• Familiarity with MLOps best practices, including version control, HPC environments, and experiment tracking
• Ability to develop and deploy robust machine learning pipelines for scientific workflows
• Soft Skills: Excellent communication, collaboration, and analytical thinking.

Preferred Qualifications:

• Experience with medical imaging modalities (e.g., OCT, CFP, MRI, CT, X-ray, PET)
• Knowledge of models such as Unet, DeepLab, Vision Transformers (ViT), SAM, and Detectron
• Familiarity with experiment tracking tools like Weights & Biases (W&B)

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