Staff AI/ML Engineer - Controllable Biology in Heidelberg

Business Introduction At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting‑edge technology to transform people’s lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients’ needs and have the highest probability of success. We’re uniting science, technology, and talent to get ahead of disease together. Find out more: Our approach to R&D

Job Title: Staff AI/ML Engineer - Controllable Biology

Job Purpose: The AI/ML Controllable Biology Team applies machine learning and AI methods to biological networks and sequence data from large-scale human genetic, functional genomic, and single‑cell experiments. Models that control biological networks have the potential to be transformative in drug discovery, empowering us to find new life‑saving medicines.

Competitive candidates will have a track record of developing SOTA deep learning models to solve challenging real‑world scientific problems. You should be an outstanding scientist with in‑depth knowledge of modern machine learning. You can convert vaguely described biological and 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, and benchmarking, to shipping stable, tested, performant code and services in an agile environment. 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.

Key Responsibilities

• Convert complex biological questions into tractable mathematical problems that can be solved by modern computational methods.
• Be adept at decomposing large problems into quarterly, measurable results and consistently working towards delivering these through engineering sprints.
• Be a technical mentor in a multidisciplinary engineering team, including delegating tasks to junior colleagues and guiding them through delivery, while fostering an inclusive, supportive team culture.
• Be comfortable demoing early and often, balancing research and engineering velocity.
• Be a standard‑bearer for machine learning, software engineering, code review and agentic development best practices within the organisation.
• Define technical strategy and roadmaps for AI/ML products, balancing scientific needs, safety, and operational reliability.
• Operate in a transparent way, communicating clearly and accurately to leadership and the broader organisation.
• Partner with stakeholders to ensure models are explainable, safe, and relevant.

Basic Qualifications

• Master’s degree in a related field (e.g. computer science, mathematics or natural sciences).
• 7+ years’ experience with standard deep learning algorithms, model architectures, machine learning best practices, scalable training and deployment.
• 7+ years’ experience in software development, including code reviews, version control systems, CI/CD pipelines, software testing, technical documentation and Agile delivery methodologies.
• 5+ years’ experience in a technical leador engineering manager role with direct reports, mentoring software engineers or machine learning practitioners.
• 7+ years’ experience with Python and PyTorch, or an equivalent machine learning framework.
• Experience working with biological sequence and network data, including genomics, transcriptomics, proteomics, gene regulatory networks or related biological datasets.
• Experience collaborating with stakeholders across multiple teams, functions and geographic regions.

Preferred Qualifications

• PhD in a quantitative or computational field.
• Background in modelling disease biology, systems biology, molecular biology and biochemistry.
• Track record of delivering high‑quality, research‑level machine learning and robust software solutions.
• Peer‑reviewed publications in major AI conferences.

Work Arrangements

The role is hybrid, requiring on‑site work 2 days per week. Remote or fully home‑working arrangements are not available for this role.

Skills

• Artificial Intelligence (AI)
• Artificial Intelligence Ethics
• Artificial Neural Networks (ANNS)
• Classification Models
• Deep Learning
• Intelligent Automation (IA)
• Machine Learning (ML)
• Model Evaluation
• Predictive Modeling
• Python (Programming Language)
• Test Documentation

Salary

• If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or SanFrancisco, CA, the annual base salary for new hires in this position ranges $200,475 to $334,125. 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.
• Germany Salary Range / Gehaltsbandbreiten Deutschland: EUR 109,500 to EUR 182,500
• The annual gross base salary range for new hires in this position is listed above for each applicable location. These ranges take into account a number of factors including the candidate’s skills, experience, education level and the market rate for the role.
• In addition, this position may offer an annual bonus, Urlaubsgeld, betriebliche Altersvorsorge sowie die Berechtigung zur Teilnahme an unserem aktienbasierten Long‑Term Incentive‑Programm. Dies ist abhängig von der Rolle. Detailliertere Informationen zum gesamten Vergütungspaket werden während des Rekrutierungsprozesses bereitgestellt.
• Salary ranges for other locations are shown because some markets have pay transparency laws that require salary information on job postings, and those locations are potential job sites for this role. If salary ranges are not displayed in the job posting for a specific location or country, the relevant compensation will be discussed during the recruitment process. Please note salaries vary by country based on the candidate’s skills, experience, education level and the market rate for the role. Offers are typically made within the advertised range based on the candidate’s skills, experience and qualifications, with the upper end generally reserved for highly experienced candidates or other exceptional circumstances aligned with these criteria.
• Der jährliche Brutto - Grundgehaltsrahmen für Neueinstellungen in dieser Position ist oben für jeden relevanten Standort ausgewiesen. Diese Gehaltsspannen berücksichtigen eine Reihe von Faktoren, basierend auf den Fähigkeiten, der Berufserfahrung, der Ausbildung und Qualifikation der Kandidat*innen sowie der marktüblichen Vergütung für diese Rolle. Zusätzlich kann diese Position u.a. einen jährlichen Bonus, Urlaubsgeld, betriebliche Altersvorsorge sowie die Berechtigung zur Teilnahme an unserem aktienbasierten Long‑Term Incentive‑Programm beinhalten; dies ist abhängig von der Rolle. Detailliertere Informationen zum gesamten Vergütungspaket werden während des Rekrutierungsprozesses bereitgestellt.

Benefits

• 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.

Employment support and policies

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at DE.Contact‑Recruitment@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.

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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. Getting ahead means preventing disease as well as treating it, and we aim to impact the health of 2.5 billion people around the world in the next 10 years. 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. Find out more on our career site.