At a Glance
- Tasks: Drive the development of machine learning models for drug discovery and structural biology.
- Company: Leading biotech firm focused on innovative drug discovery solutions.
- Benefits: Competitive salary up to £130,000, early equity, and flexible remote work.
- Other info: Fully remote role with opportunities for mentorship and collaboration.
- Why this job: Make a real impact in healthcare by advancing cutting-edge ML technologies.
- Qualifications: Expertise in machine learning, particularly in protein structure prediction.
The predicted salary is between 78000 - 130000 € per year.
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., 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 our 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 our customers. You will be involved in the full project pipeline, from scoping through to results delivery and dissemination.
- 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.
- Drive external impact through high-quality open-source contributions and scientific publications.
Fully Remote Working Culture. 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 Machine Learning Engineer - Remote employer: Owen Thomas | Pending B Corp™
Join a pioneering company in the drug discovery sector, where your expertise as a Senior Forward-Deployed Machine Learning Engineer will directly influence groundbreaking advancements in structural biology. Enjoy a fully remote working culture that promotes flexibility and work-life balance, alongside competitive compensation, early equity opportunities, and a collaborative environment that fosters mentorship and professional growth. This is an exceptional opportunity to contribute to meaningful projects while working with leading academic and industry partners in a fast-paced startup atmosphere.
Contact Detail:
Owen Thomas | Pending B Corp™ Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer - Remote
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to protein structure prediction. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨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 stakeholders.
✨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 who are eager to make an impact in drug discovery.
We think you need these skills to ace Senior Machine Learning Engineer - Remote
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Machine Learning Engineer. Highlight your experience with protein structure prediction and any relevant projects that showcase your skills in ML. We want to see how your background aligns with our needs!
Showcase Your Impact:When writing your application, focus on the impact you've made in previous roles. Use specific examples of how your work has advanced drug discovery or improved ML systems. We love seeing quantifiable results!
Be Clear and Concise:Keep your application clear and to the point. Avoid jargon unless it's necessary, and make sure your passion for structural biology and machine learning shines through. We appreciate straightforward communication!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
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 training and deploying state-of-the-art models, especially in protein structure prediction. Be ready to explain how these models fit into drug discovery workflows and share specific examples of your past work.
✨Showcase Your Problem-Solving Skills
Prepare to break down complex technical problems during the interview. Think of a few scenarios where you've successfully tackled challenging issues in ML systems, and be ready to walk the interviewers through your thought process and solutions.
✨Engage with the Team's Vision
Research the company’s mission and recent projects. Be prepared to discuss how your expertise aligns with their goals in drug discovery and structural biology. Showing that you understand their vision will demonstrate your genuine interest in the role.
✨Prepare for Technical Case Studies
Since the role involves leading comprehensive technical case studies, practice explaining your approach to project scoping, data selection, and benchmarking strategies. Be ready to discuss how you would manage the lifecycle of a project from start to finish.
