Lead AI/ML Engineer

GlaxoSmithKline
Cambridge
1 month ago
Applications closed

Related Jobs

View all jobs

ML (Machine Learning) Engineer

MLOps Engineer (UKIC DV Cleared)

Machine Learning Product Engineer (Hybrid)

Senior Director Artificial Intelligence/Machine Learning

Director of Artificial Intelligence - Manufacturing & Industrial

AI Project Manager

Site Name:Cambridge 300 Technology Square, San Francisco, Seattle Sixth Ave, USA - Pennsylvania - Upper Providence
Posted Date:Mar 6 2025

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. If that excites you, we'd love to chat.

The AI/ML Biomedical AI Team applies machine learning and AI methods to questions at the start and end of the journey of drug development. Our viral evolution group is focused on applying these techniques to support the development of cutting-edge treatments and prevents for viral diseases like Influenza, RSV, and COVID-19. We wish to see humanity fully realize the potential of new platforms like mRNA vaccines, oligonucleotides, and monoclonal antibodies when combating infectious diseases. To do so we model viral evolution using large scale datasets and emerging AIML techniques.

We are looking for a Lead AI/ML Engineer to help us make this vision a reality. Competitive candidates will have a track record in developing SOTA deep learning models for solving challenging real world scientific problems. You should be an outstanding scientist with in-depth knowledge in modern machine learning. You can convert vaguely described biological/drug discovery challenges into well-defined machine learning problems. You can independently execute and deliver full AI/ML driven solutions from sourcing training data, designing and implementing SOTA machine learning models, testing, benchmarking, and product-driven research for model performance improvement, to shipping stable, tested, performant code and services in an agile environment. You are on team null hypothesis, focused on delivering well-vetted tools with clearly defined limitations. Your expertise in protein and RNA-language modelling will be valued.

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.

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

  • Doctoral degree in Computer Science or Applied Math, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history. Candidates with graduate studies in CS and biological sciences or equivalent work history will be highly competitive.
  • Experienced in developing deep learning models.
  • A scientist, machine learning engineer, and software engineer with expertise and depth in at least one area.
  • Experience with standard deep learning algorithms and model architectures.
  • Familiarity with current deep learning literature and math of machine learning.
  • Knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation.
  • Experience in PyTorch, Tensorflow, or other deep learning frameworks.
  • Experienced/accomplished in software engineering with advanced skills in python and/or C++.
  • Experience with devops stacks: version control, CI/CD, containerization, etc.
  • At least one peer-reviewed publication.

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

  • PhD in Machine Learning.
  • Expertise in protein or RNA language models.
  • Knowledge in disease biology, molecular biology, and virology.
  • Experience with biological data (e.g., genomics, transcriptomics, epigenomics, proteomics).
  • Peer-reviewed publications in major AI conferences.
  • Experience in design, development, and deployment of commercial AI/ML software.
  • Track record of contributing to open-source projects.
  • Mentality of commit early and often, metrics before models, and shipping high-quality production code.

The annual base salary for new hires in this position ranges from $0 to $0 taking 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.

Please visitGSK US Benefits Summaryto 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 special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/immunology and oncology).

Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).

GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.