ML Engineer Jobs in USA with Visa Sponsorship

Site Name: Cambridge 300 Technology Square, London The Stanley Building, South San Francisco 611 Gateway Blvd
Posted Date: Mar 2 2026

At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI. The opportunities for machine learning extend to many other areas of our business, including medicine safety, manufacturing, and supply chain. To realize these opportunities, GSK has created a global Artificial Intelligence and Machine learning group (AI/ML), with locations in London, San Francisco, Boston, Philadelphia, and Heidelberg, to focus on the development and application of machine learning to problems of critical importance at GSK. We possess a world-leading data and computational environment (including specialist hardware) to enable large-scale, scientific experiments that exploit GSK’s unique access to data. By actively engaging with the machine learning community and publishing our research, code and models built on public data, the AI/ML group operates at the cutting-edge of machine learning research. To help us, we seek a passionate researcher who wishes to turn their talents to the application of causal machine learning to the healthcare sector. You will be working with multiple Research Engineers on building products to support multiple large-scale projects within AI/ML. In addition, the researcher will learn about the pharmaceutical industry and software engineering and translate their research into tools that aid discovery and development of transformational medicines and vaccines. You will have access to outstanding experts in biology, clinical and translational research, chemistry, (software) engineering, data science and machine learning; unrivalled data sources and GSK’s state-of-the-art laboratory and compute infrastructure to help you develop and validate your machine learning research.

As a Machine Learning Engineer focusing on applications in oncology, you will be expected to:

- Design and implement novel scientific approaches for biophysical modeling and foundation model-driven analysis of multi-modal clinical and genomic data for biomarker and target discovery to improve patient selection and enable next-generation assets.
- Design, develop, and implement analytical solutions using a variety of commercial and open-source tools (common tools include PyTorch and scikit-learn).
- Connect and collaborate with subject matter experts in biology, genomics, and medicine.
- Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models.
- Develop and embed automated and agentic processes for predictive model validation, deployment, and implementation.
- Deploy your algorithms to production to identify actionable insights from large databases.

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:
- Master’s degree in computer science, applied math, statistics, physics, systems biology, computational biology, bioinformatics, or related field
- Experience in Python programming and knowledge in machine learning, statistics, and applied math.
- Familiarity with modern machine learning methods (generative models, representation learning)
- Experience in building deep learning models, preferably with exposure to biophysical modeling, functional genomics, molecular and cellular biology or to modeling dynamical systems
- Experience with at least one Deep Learning framework such as PyTorch

Preferred Qualifications:

If you have the following characteristics, they would be a plus:
- PhD in computer science, applied mathematics, statistics, physics, systems biology, computational biology, bioinformatics, or a related field.
- Experience in analyzing real-world and/or clinical data.
- Experience in incorporating agentic models into ML workflows
- Understanding of best practices in software engineering, including training and operating algorithms at scale, and production deployment of ML services.
- Knowledge of cancer biology and precision oncology.
- Excellent written and verbal communication skills.
- Ability to digest, synthesize, and implement innovative methods from scientific literature.
- Ability to solve complex problems using creative approaches, state-of-the-art tools, and best engineering practices.
- Ability to work autonomously and collaboratively as part of a team, both teaching and learning every day.
- High impact publications at venues such as NeurIPS, ICML, ICLR etc. would be a plus
- Publication in natural sciences would be a plus

If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $136,125 to $226,875. The US salary ranges take into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process. Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale. People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at HR.AmericasSC-CS@gsk.com where you can also request a call. Please note should your inquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

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Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements. For more information, please visit the Centers for Medicare and Medicaid Services (CMS) website at https://openpaymentsdata.cms.gov/