ML Research Engineer/Scientist
London
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingAs an ML Research Engineer/Scientist, you will develop the next generation of machine learning models and algorithms that power Boltz Lab and expand what scientists can do with AI in molecular modeling and design.
You’ll collaborate closely with an interdisciplinary team of ML researchers, domain experts in chemistry and biology, and software engineers.
You’ll collaborate closely with an interdisciplinary team of ML researchers, domain experts in chemistry and biology, and software engineers.
From the employer’s posting
As an ML Research Engineer/Scientist, you will develop the next generation of machine learning models and algorithms that power Boltz Lab and expand what scientists can do with AI in molecular modeling and design.
You’ll collaborate closely with an interdisciplinary team of ML researchers, domain experts in chemistry and biology, and software engineers. Together, you’ll design new model architectures, training objectives, and the high-quality datasets required to train them, pushing performance on fundamental tasks in drug discovery. You’ll also help define how we evaluate progress, building rigorous benchmarks and validation pipelines that connect offline metrics to real-world outcomes.
As an ML Research Engineer/Scientist, you will develop the next generation of machine learning models and algorithms that power Boltz Lab and expand what scientists can do with AI in molecular modeling and design. You’ll collaborate closely with an interdisciplinary team of ML researchers, domain experts in chemistry and biology, and software engineers. Together, you’ll design new model architectures, training objectives, and the high-quality datasets required to train them, pushing performance on fundamental tasks in drug discovery. You’ll also help define how we evaluate progress, building rigorous benchmarks and validation pipelines that connect offline metrics to real-world outcomes. This role is for someone who is a mission-driven technical leader who wants to push the frontier and then turn that progress into capabilities that thousands of scientists can use. You’ll set direction as well as execute while holding a high bar on scientific rigor, strong engineering practices and real-world impact.
What you’ll bring
All qualificationsCore experience
- Experience contributing to and maintaining deep-learning codebases, with a high bar for engineering quality, reproducibility, and testing.
- Experience training, scaling, and evaluating large models on applied, real-world problems, including building reliable evaluation suites and diagnosing failure modes.
- Experience working in an interdisciplinary scientific environment, especially across ML, biology, chemistry, and physics.
- Familiarity with the tools, data formats and workflows commonly used in computational biology and chemistry.
Qualification wording
Experience contributing to and maintaining deep-learning codebases, with a high bar for engineering quality, reproducibility, and testing.
Experience training, scaling, and evaluating large models on applied, real-world problems, including building reliable evaluation suites and diagnosing failure modes.
Experience working in an interdisciplinary scientific environment, especially across ML, biology, chemistry, and physics.
Familiarity with the tools, data formats and workflows commonly used in computational biology and chemistry.
Tools in this posting
- Python
- NumPy
- pandas
- PyTorch
- Scipy
Source — Tool mentions in context
- Demonstrated strength in deep learning research and development, including designing new architectures, running rigorous experiments, and performing careful analysis. - Strong hands-on experience with PyTorch and the scientific Python ecosystem (NumPy, SciPy, Pandas, etc.). - Experience contributing to and maintaining deep-learning codebases, with a high bar for engineering quality, reproducibility, and testing.
About Boltz
We provide the compute, the scalable infrastructure, and the collaboration layer, so scientists can iterate faster and stay focused.
In the employer’s words · Read in context
Job description
About Boltz
Boltz is a public benefit company building the next generation of AI-powered molecular modeling tools to make biology programmable and accelerate drug discovery, while keeping frontier capabilities broadly accessible.
Boltz-1, Boltz-2, and BoltzGen are open models trusted by 100,000+ scientists across biotech and academia, and used in programs at every Top 20 pharma as well as leading agrichemical and industrial research organizations.
We deliver these capabilities through Boltz Lab, our platform for running our latest models and design agents as reliable, production-grade tools. Boltz Lab is designed around real chemistry and biology workflows, so teams can start from a target and a hypothesis and quickly generate, evaluate, and rank candidate molecules. We provide the compute, the scalable infrastructure, and the collaboration layer, so scientists can iterate faster and stay focused.
You can read more about our mission, research and product vision on our manifesto.
About the role
As an ML Research Engineer/Scientist, you will develop the next generation of machine learning models and algorithms that power Boltz Lab and expand what scientists can do with AI in molecular modeling and design.
You’ll collaborate closely with an interdisciplinary team of ML researchers, domain experts in chemistry and biology, and software engineers. Together, you’ll design new model architectures, training objectives, and the high-quality datasets required to train them, pushing performance on fundamental tasks in drug discovery. You’ll also help define how we evaluate progress, building rigorous benchmarks and validation pipelines that connect offline metrics to real-world outcomes.
This role is for someone who is a mission-driven technical leader who wants to push the frontier and then turn that progress into capabilities that thousands of scientists can use. You’ll set direction as well as execute while holding a high bar on scientific rigor, strong engineering practices and real-world impact.
About you
Essentials:
- Extensive publication record in top-tier ML or life-science conferences and journals (NeurIPS, ICLR, ICML, Nature Methods, and related).
- Demonstrated strength in deep learning research and development, including designing new architectures, running rigorous experiments, and performing careful analysis.
- Strong hands-on experience with PyTorch and the scientific Python ecosystem (NumPy, SciPy, Pandas, etc.).
- Experience contributing to and maintaining deep-learning codebases, with a high bar for engineering quality, reproducibility, and testing.
Nice to have:
- Experience training, scaling, and evaluating large models on applied, real-world problems, including building reliable evaluation suites and diagnosing failure modes.
- Experience working in an interdisciplinary scientific environment, especially across ML, biology, chemistry, and physics.
- Familiarity with the tools, data formats and workflows commonly used in computational biology and chemistry.
What we offer
- Opportunity to drive outsized real-world impact by building tools that empower thousands of scientists across the industry.
- Work alongside one of the most talent-dense teams in the field.
- Significant ownership and independence, with responsibility for driving projects from concept to deployment.
- Highly competitive salary with substantial equity ownership.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on jobs.gem.com. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
London
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- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 51
- Last seen by us
- Oct 2, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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