At a Glance
- Tasks: Drive drug discovery with cutting-edge machine learning models and collaborate on impactful projects.
- Company: Leading biotech firm focused on innovative drug discovery solutions.
- Benefits: Up to £130,000 salary, equity options, remote work, and flexible hours.
- Why this job: Make a real difference in healthcare by advancing machine learning in drug discovery.
- Qualifications: Expertise in ML models for protein structure prediction and strong problem-solving skills.
- Other info: Fully remote role with excellent career growth and mentorship opportunities.
The predicted salary is between 78000 - 104000 £ per year.
The Client: A leading organization in the drug discovery field is currently looking for a Senior Forward-Deployed Machine Learning Engineer to drive the development of foundational models that directly impact real-world drug discovery workflows. This hands-on, high-impact role offers the opportunity to advance the application of foundational models to complex structural biology challenges. The successful candidate will work closely with the leadership team, serving as the technical authority on machine learning modeling, architecture, and experimentation in this domain. While this role does not involve people management, the candidate will be expected to provide mentorship and guidance to engineers and researchers on technical content. The ideal candidate brings deep expertise in training and deploying state-of-the-art models for protein structure prediction. Beyond technical proficiency, you must understand how these models integrate into broader drug discovery pipelines and possess the strategic mindset needed to break down complex problems into actionable, impactful ML solutions.
Requirements:
- Proven experience building and training contemporary models (e.g., AlphaFold, OpenFold, Boltz) at scale in a production environment.
- A strong track record of applying ML to real-world protein structure prediction or drug discovery problems.
- Comfortable in a fast-paced startup environment, with the ability to break down complex technical problems into impactful ML systems.
- Experience in Federated Learning, privacy-preserving ML, or a portfolio of publications in top-tier journals/conferences like NeurIPS, ICML, or Nature Methods.
- Work with customers and academic partners to define data, preprocessing, selection, and benchmarking strategies for novel training tasks involving protein structures, complexes, and multimodal biological data.
- Carry out case studies associated with the above, providing scientific and technical expertise to customers.
Responsibilities:
- Advance the state-of-the-art by fine-tuning and customizing foundational architectures such as OpenFold, ESMFold, and Boltz-2 for specialized structural biology challenges.
- Architect model extensions tailored for binding affinity and protein complex prediction, overseeing everything from data distillation to rigorous benchmarking.
- Partner with leading academic and industry stakeholders to engineer data selection and preprocessing strategies for complex, multimodal biological datasets.
- Lead comprehensive technical case studies, managing the entire lifecycle from initial project scoping to the final dissemination of results.
- Develop and sustain high-scale ML pipelines that support efficient training, inference, and production-grade deployment.
- Work across internal teams to ensure all model development is anchored in solving genuine drug discovery hurdles.
- Drive external impact through high-quality open-source contributions and scientific publications.
Remuneration:
- Fully Remote Working Culture
- Up to £160,000 Base Salary
- Attractive Stock Options
- B2B & Full-time employee options
- Flexible hours + - 3 hours of CET time zone
If you think you are a good match for the Senior Forward-Deployed Machine Learning Engineer role, ping us over your CV and we will give you a call if we think you are a good match!
Senior Forward-Deployed Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A - Drug discovery B2B Platform | EU Remote | | Salary Up to £130,000K, plus early equity+benefits in West End employer: Owen Thomas | Pending B Corp™
Contact Detail:
Owen Thomas | Pending B Corp™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Forward-Deployed Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A - Drug discovery B2B Platform | EU Remote | | Salary Up to £130,000K, plus early equity+benefits in West End
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at conferences. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to protein structure prediction or ML models. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical teams.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Senior Forward-Deployed Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A - Drug discovery B2B Platform | EU Remote | | Salary Up to £130,000K, plus early equity+benefits in West End
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning models, especially in structural biology. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about drug discovery and how your expertise can contribute to our mission. Keep it engaging and personal – we love a good story!
Showcase Your Technical Skills: Be specific about the tools and technologies you’ve used in your previous roles. Mention any experience with foundational models like AlphaFold or OpenFold, as well as your understanding of ML integration in drug discovery workflows. We’re keen to see your technical prowess!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture!
How to prepare for a job interview at Owen Thomas | Pending B Corp™
✨Know Your Models Inside Out
Make sure you can discuss your experience with models like AlphaFold and OpenFold in detail. Be ready to explain how you've applied these models to real-world protein structure prediction problems, as this will show your deep technical expertise.
✨Understand the Bigger Picture
It's crucial to demonstrate how your machine learning solutions fit into broader drug discovery pipelines. Prepare examples of how you've broken down complex problems into actionable ML strategies that have had a tangible impact on projects.
✨Showcase Your Collaborative Spirit
Since you'll be working closely with customers and academic partners, highlight your experience in defining data selection and preprocessing strategies. Share specific instances where collaboration led to successful outcomes in your previous roles.
✨Prepare for Technical Case Studies
Expect to discuss case studies related to your work. Be ready to walk through the entire project lifecycle, from scoping to results delivery, and emphasise your role in managing these processes effectively.