AI/ML Engineer - Phenomics

Role Summary

AI/ML Engineer - Phenomics at GSK. Join the AI/ML Phenomics Team to apply cutting-edge machine learning and AI methodologies to generate insights from multi-modal high-content data modalities, including spatial transcriptomics, high-dimensional imaging, and multi-omics readouts in in vitro systems.

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 in high-throughput data.
• Leverage high-performance computing clusters and cloud compute to train and productionize models at scale.
• Collaborate with domain experts to generate actionable insights that impact target identification, hit identification, and safety testing.
• Contribute to the codebase with well-tested, production-ready code.

Qualifications

• PhD or master's 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 with developing, implementing, and training deep learning models with PyTorch, TensorFlow, or other frameworks.
• 2+ years of experience in cell imaging (required for master's degree holders).

Skills

• Experience with high-content imaging and diverse multi-omics (preferred).
• Knowledge in disease biology, molecular biology, and biochemistry (preferred).
• Track record of writing software in a team in industrial environments or open-source projects (preferred).
• Publications or projects at the intersection of machine learning and life sciences (preferred).
• Commit early, metrics-driven, and shipping high-quality production code (preferred).

Education

• PhD or master's in relevant field as specified above (required/preferred per bullet).

Additional Requirements

• Location details: USA - California - San Francisco; Cambridge, MA; London (UK) - The Stanley Building; Hertfordshire - Stevenage; USA - Pennsylvania - Upper Providence.