Machine Learning Engineer, GSK

Oligonucleotide Therapeutics, US

$130.9-177.1k

+ Annual bonus

SQL

Python

Tensorflow

PyTorch

Git

Junior, Mid and Senior level

San Francisco Bay Area

2-5 days a week in office

Building a cutting-edge digital and tech team.

Job no longer available

Building a cutting-edge digital and tech team.

1001+ employees

HealthcareArtificial IntelligenceBig dataMachine LearningCyber SecurityData IntegrationDevOpsCloud ComputingBiotechnology MedTech

Job no longer available

$130.9-177.1k

+ Annual bonus

SQL

Python

Tensorflow

PyTorch

Git

Junior, Mid and Senior level

San Francisco Bay Area

2-5 days a week in office

1001+ employees

HealthcareArtificial IntelligenceBig dataMachine LearningCyber SecurityData IntegrationDevOpsCloud ComputingBiotechnology MedTech

Company mission

At GSK, we use technology to deliver what matters most, better and faster. Whether it’s life-saving medicines or life-enhancing products, Tech at GSK helps scale and accelerate our expertise.

Job

Company

Role

Who you are

Familiarity and experience with genomics and RNA biology is a plus, but not required
This position is open to machine learning engineers with a track record of excellence in other domains who have a desire to learn
Strong candidates will have a track record of shipping high performing AI/ML powered products, academic excellence, and a passion for solving challenging problems in Artificial Intelligence and Machine Learning
Education in the biological sciences is a plus but is not necessary; passion to help therapies for new and existing diseases, and a pattern of continuous learning and development is mandatory
Degree in a quantitative or engineering discipline (computer science, bioengineering, physics, mathematics, electrical engineering, etc) or equivalent work experience
Experience in major deep learning framework (Pytorch, Tensorflow)
Programming expertise in Python
Experience with fundamental components of AIML engineering stack (Git, SQL, Shell Scripting)
Knowledge of machine learning best practices

Desirable

Internship experience as researcher in AIML focused academic lab or AIML engineer or SWE in industry
Experience working with biomedical datasets (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images)
Track record of contributing to open-source projects
Mentality of commit early and often, metrics before models, and shipping high quality production code

What the job involves

At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects
It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI
We're looking for an accomplished Machine Learning Engineer to help make this vision a reality
In this role, you will build and deploy machine learning models to accelerate the development of oligonucleotide therapeutics
You will work with foundational genomics models and multiomics datasets from patients and lab experiments to model aspects of RNA biology that will inform our understanding the molecular mechanisms of diseases, drug response, and design of best-in-class drugs in a new and exciting therapeutic modality
The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration
We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one

Our take

GSK Tech is set to build a suite of next-generation platforms for data- and prediction-driven drug discovery in support of GSK's Research and AI/ML organizations, and an industry-leading data engineering function in support of AI/ML and Genomic Sciences.

GSK’s ambitions go far past the data lake: they’re building a comprehensive data and machine learning ecosystem that can speak to the customers in their own scientific and technical language and semantics. Enabled by GSK Knowledge Graph, powered by machine learning, and underpinned by natural language processing, GSK's vision is for accessibility to data (and, importantly, the knowledge it represents). GSK wants to increase this tenfold, taking mere moments to find, access, and integrate the right information.

The creation of GSK Tech shows GSK's commitment to making a major investment in changing how we think about data in the research space, and levelling up the data experience for GSK's researchers, scientists, computational scientists, AI/ML Engineers, and ultimately decision-makers. As of 2024, GSK is putting more energy into its Cyber Security features, thus widening its market reach.

Steph

Company Specialist at Welcome to the Jungle

Insights

45% female employees

6% employee growth in 12 months

Glassdoor (4.1)

Company

Company benefits

An annual bonus based on company performance
Access to healthcare and wellbeing programmes, pension plan membership, savings programmes, time off and childcare support
Employee recognition programmes which reward exceptional achievements
Long term incentives through share ownership link your rewards to our longer term performance
Coaching, mentoring and formal training programmes
Plenty of opportunities for open conversations with people who can help to shape your career
A range of health and wellbeing programmes and support services to help employees understand how to feel healthier, happier and more energised at work and at home

Company HQ

Brentford, UK

Leadership

Luke Miels

(CEO)

Luke became CEO on Jan 1, 2026, after serving as CEO designate since Sept 2025. He joined GSK in 2017 as Chief Commercial Officer, responsible for our commercial portfolio of medicines and vaccines.

Shobie Ramakrishnan

(Chief Digital and Technology Officer)

Has a broad experience in biotech and hi-tech companies. Has led Digital and Technology for GSK’s Global Commercial organisation, transforming the company’s capabilities in digital, data & analytics.

Michael Elmore

(SVP & Global Chief Information Security Officer)

Experienced in building and leading tech teams across cyber security, IT infrastructure, application development, and more. A trusted advisor to VCs and startups focusing on cybersecurity advancements.

Shubha Chaudhari

(SVP, Development Digital & Tech)

Previously worked at Novartis in several roles, including Head of Clinical Informatics, Global Head of Development Informatics, and Head of Digital Transformation.

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