At a Glance
- Tasks: Lead innovative ML research to revolutionise drug discovery and create impactful solutions.
- Company: Join SandboxAQ, a cutting-edge AI company tackling global challenges.
- Benefits: Enjoy competitive pay, comprehensive benefits, and flexible work arrangements.
- Other info: Collaborate with a diverse team of experts in a dynamic, growth-focused environment.
- Why this job: Make a real difference in biopharma with your expertise in ML and deep learning.
- Qualifications: PhD in relevant field and proven experience in ML and drug discovery.
The predicted salary is between 80000 - 100000 £ per year.
Location: United Kingdom
Employment Type: Full time
Department: AI Simulation
Compensation: At SandboxAQ, we are committed to competitive, equitable, and transparent compensation; we continuously benchmark our salaries and total compensation to premium markets to ensure our competitiveness. Individual pay within the above range is determined by job-related skills, experience, education, and geographic location. With a focus on pay equity and ensuring opportunity for future salary progression, our typical practice is to hire within the first half of the base salary range for a given role and level. This approach allows us to reward performance and increasing expertise consistently as your career develops with us.
About SandboxAQ: SandboxAQ is a high‑growth company delivering AI solutions that address some of the world’s greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth‑backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving global workforce poised to tackle the world’s epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like‑minded people who value entrepreneurialism, ownership, and transformative impact.
The Opportunity: The AI Sim R&D team creates leading edge ML and physics‑based models ("LQMs") to advance drug and materials discovery. We are a flexible, creative, and impact driven team of multidisciplinary scientists and engineers, whose products dramatically accelerate the creation of molecules and medicines. As a Staff ML Research Scientist focusing on Co‑Folding & Affinity, you will occupy a senior position architecting our ML biopharma capabilities. Your central purpose is to redefine the state‑of‑the‑art in structure prediction and binding affinity, transforming these breakthroughs into core components of our software suite. Within your first year, you will: pioneer novel deep learning architectures that surpass current benchmarks, orchestrate the seamless integration of these models into production‑ready drug discovery pipelines, and solidify SandboxAQ’s scientific authority through high‑impact publications and industry‑shaping research.
Key Responsibilities:
- Pioneer Novel Architectures: Drive the research and development of next‑generation deep learning models for protein‑ligand co‑folding and affinity prediction.
- Architect Product Integration: Bridge from research to commercial utility by equipping SandboxAQ’s software products with advanced predictive capabilities.
- Orchestrate Technical Strategy: Bring novel ideas and the content of scientific papers into the ideation, training, and benchmarking of complex models, ensuring they are optimized for large‑scale, real‑world drug discovery applications.
- Champion Scientific Excellence: Act as a technical beacon for the team, representing SandboxAQ scientifically and shaping its vision externally and internally.
- Scale High‑Performing Teams: Mentor junior researchers and collaborate across engineering and product teams to foster a culture of technical rigor and rapid iteration.
World‑Class Domain Expertise: PhD in Computer Science, Computational Chemistry, or a related field, with specific focus on structure‑based deep learned affinity modelling a plus.
Proven Industrial Impact: At least 4 years of post‑PhD experience, including experience in a professional industry setting, with a track record of delivering scientific impact that translates to product.
Frontier Technical Skills: Direct, hands‑on experience developing and executing leading‑edge co‑folding and/or affinity prediction models, from proof of concept to productionized workflows.
Domain‑Specific Excellence: Proven excellence in co‑folding and/or affinity prediction, as demonstrated by participation in industrial projects and/or academic publications.
Professional Engineering Fluency: Experience functioning within a professional software team, including proficiency in Python and modern ML frameworks (PyTorch/JAX) at scale.
Highly Desired Skills & Experience:
- Postdoctoral Experience: In deep learned structure‑based affinity models.
- Commercial Success: Experience shipping commercial‑grade software products within the biopharma or tech sectors.
- Interdisciplinary Leadership: Relevant postdoctoral experience that demonstrates an ability to lead research at the intersection of AI and physical sciences.
- Deep Biopharma Context: Direct experience working within drug discovery pipelines, understanding the specific challenges of lead optimization and hit‑to‑lead phases.
- Technical Vision: Experience setting the technical roadmap for a specialized research group or project.
- Research Visibility: A track record of contributions to the scientific community, such as first‑author publications in top‑tier venues like NeurIPS, ICML, or CVPR.
- Agentic Coding: Deep familiarity with agentic coding tools (e.g. Claude code, Codex).
Why Join Us?
We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. Compensation: Competitive base salary, performance‑based incentives or bonuses (where applicable), and equity participation. Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family‑building benefits. Work‑Life Balance: Flexible paid time off, company‑wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. Career Development: Opportunities for continuous learning and growth through on‑the‑job development, cross‑functional collaboration, and access to internal learning and development programs.
SandboxAQ Welcomes All: We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.
Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.
Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.
Staff ML Research Scientist, Co-Folding and Affinity in London employer: Sandboxaq
At SandboxAQ, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters creativity and collaboration. Our commitment to competitive compensation, comprehensive benefits, and professional growth opportunities ensures that our employees thrive both personally and professionally. Located in the UK, we provide a flexible work environment that supports work-life balance, empowering our team to tackle some of the world's greatest challenges in AI and biopharma.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Research Scientist, Co-Folding and Affinity in London
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and research. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to ML and biopharma. We recommend doing mock interviews with friends or mentors to boost your confidence.
✨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, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Staff ML Research Scientist, Co-Folding and Affinity in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Staff ML Research Scientist role. Highlight your experience in deep learning, co-folding, and affinity prediction. We want to see how your skills align with our mission at SandboxAQ!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and drug discovery, and explain why you’re excited about joining our team. Let us know how you can contribute to our innovative projects.
Showcase Your Research Impact:Don’t forget to include any publications or projects that demonstrate your expertise in ML and biopharma. We love seeing candidates who have made a real impact in their field, so show us what you've got!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the SandboxAQ family!
How to prepare for a job interview at Sandboxaq
✨Know Your Stuff
Make sure you’re well-versed in the latest advancements in ML and biopharma. Brush up on your knowledge of protein-ligand co-folding and affinity prediction, as well as any recent publications in top-tier venues. This will not only show your expertise but also your passion for the field.
✨Showcase Your Impact
Prepare to discuss specific projects where you've made a significant impact. Highlight your experience in developing deep learning models and how they translated into real-world applications. Use metrics or outcomes to illustrate your contributions, as this will resonate well with the interviewers.
✨Be Ready to Collaborate
Since the role involves mentoring and collaborating across teams, be prepared to discuss your approach to teamwork. Share examples of how you've successfully worked with engineers and product teams in the past, and how you foster a culture of technical rigor and rapid iteration.
✨Ask Insightful Questions
Prepare thoughtful questions that demonstrate your interest in SandboxAQ’s mission and the AI Sim R&D team. Inquire about their current challenges in drug discovery or how they envision the future of ML in biopharma. This shows you're not just interested in the role, but also in contributing to their vision.
