AI/ML Engineer

$130,900 - $177,100/Yr

Disability Solutions - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

Administrative and Support Services

About the position

The AI/ML Engineer position at GSK focuses on developing and validating advanced machine learning models to address complex scientific challenges in healthcare. The role involves working with multi-modal high-content data to generate actionable insights that can impact drug development and disease treatment. The successful candidate will collaborate with cross-disciplinary teams and contribute to a codebase that supports high-performance computing and cloud-based model training.

Responsibilities

• Carry out product-driven research on novel machine learning methods to analyze terabytes of internal multi-modal high-content data.
• Design approaches to deconvolve real biological signals from confounding effects inherent in high-throughput biological data.
• Leverage internal high-performance computing cluster and cloud compute to train and productionize models at scale.
• Work closely with domain experts on cross-disciplinary teams to generate actionable insights that impact target identification, hit identification, and safety testing.
• Contribute to the developing codebase with well-tested, production-ready code.

Requirements

• Graduate studies in computer science, engineering, applied mathematics, machine learning, or equivalent practical experience.
• 2+ years of experience in machine learning and software engineering best practices.
• 2+ years of experience working in a collaborative CI/CD software development environment, including use of git.
• 2+ years of experience developing, implementing, and training deep learning models with PyTorch, Tensorflow, or other deep learning frameworks.

Nice-to-haves

• Experience working with high-content imaging and diverse multi-omics.
• Knowledge in disease biology, molecular biology, and biochemistry.
• Track record of writing software in a team in industrial environments or open-source projects.
• Track record of projects or peer-reviewed publications at the intersection of machine learning and life sciences.
• Mentality of commit early and often, metrics before models, and shipping high-quality production code.

Benefits

• Health care and other insurance benefits (for employee and family)
• Retirement benefits
• Paid holidays
• Vacation
• Paid caregiver/parental and medical leave