Machine Learning Research Engineer

Constructive Bio; Cambridgeshire and Peterborough; On-site; GBP 50,000 - 70,000; Full time

Benefits offered by this job

Employee share option plan

Private health insurance

Pension plan (matching up to 8%)

On-site parking

Job summary

A VC-backed biotechnology startup is looking for an ML engineer to develop production systems that bridge biology and machine learning. You'll implement state-of-the-art models, design experimentation infrastructures, and refine processes in a collaborative environment. The ideal candidate has a BSc or MSc in an engineering field, solid ML experience, and a deep curiosity about biology. This is an exciting opportunity to shape the future of synthetic genomics and work closely with experimental scientists.

Qualifications

• Demonstrated ML research and development experience.
• Comfortable explaining technical tradeoffs to non-ML collaborators.
• Experience in computational biology, particularly with genomic models.

Responsibilities

• Implement and benchmark state-of-the-art sequence models.
• Build robust experimentation infrastructure.
• Refactor research code into clean, manageable systems.

Skills

Production experience with PyTorch

Strong communication skills

Algorithms and data structures

Curiosity about biology

Education

BSc or MSc in engineering

Tools

Hugging Face libraries

Job description

Constructive Bio is a VC-backed biotechnology startup based in Whittlesford, Cambridge. Our unique technology turns living cells into biofactories, creating sustainable new materials and therapeutics. With full control of the genetic sequence and code, we are exploring chemical space previously unreached by natural biology.

Constructive Bio is a spinout from Professor Jason Chin's laboratory at the MRC Laboratory of Molecular Biology in Cambridge. Learn more about the Chin lab achievements here:

https://www2.mrc-lmb.cam.ac.uk/ccsb/jason-chin/

We recently secured $58 million Series A fundraising. Read more here: https://www.constructive.bio/blog/news/constructive-bio-secures-58-million-in-series-a-financing

What we’re looking for:

We're looking for an ML engineer who can turn prototypes into production systems and work fluidly across the biology-ML boundary. You'll build and maintain our codebase, scale training pipelines, and fine-tune state-of-the-art sequence models on in-house data — all in close collaboration with experimental biologists. This is a frontier role: generative models that directly inform wet-lab design cycles.

As our second ML hire, you'll work directly with our ML Scientist to define engineering standards and infrastructure that will shape everything that follows. The role carries real ownership — and real exposure to the full stack of modern biological ML.

Responsibilities

• Implement and benchmark state-of-the-art sequence models (transformers, diffusion models, language models for genomics)
• Build robust experimentation infrastructure: logging, dashboards, hyperparameter sweeps, reproducibility tooling
• Apply fine-tuning protocols on internal biological datasets
• Refactor research code into clean, modular, maintainable systems
• Identify technical gaps and propose solutions — distributed training, data pipelines, inference optimization
• Translate model outputs into formats biologists can interpret and act on; participate actively in cross-functional discussions
• Write well-documented code; participate in code reviews and help set the engineering bar

Requirements

• BSc or MSc in an engineering discipline, with demonstrated ML research and development experience
• Hands-on production experience with PyTorch and Hugging Face libraries
• Solid grasp of algorithms, data structures, and software design principles
• Strong communication skills — you're comfortable explaining technical tradeoffs to non-ML collaborators
• Curiosity about biology; willingness to engage seriously with the domain, not just tolerate it
• Experience in computational biology, particularly sequence or genomic language models
• Publications or open-source contributions in ML or bioinformatics

Why Constructive Bio

We're a small, focused team building toward a programmable biomolecules platform. As an early joiner you'll have genuine influence over technical direction, not just execution of a pre-set roadmap. You'll work at the intersection of cutting-edge ML and experimental biology, with direct line of sight from model to experiment to result.

We measure success by what works in the wet lab, not what looks good on a benchmark. You'll work directly with experimental scientists to design and test ideas, with a short feedback loop between computation and experiment. That proximity is what makes the work meaningful and demanding. Your models will be evaluated by people who understand the biology deeply, which raises the bar for what good looks like. You'll have a peer in our ML Scientist from day one, but the role requires genuine scientific engagement, not just technical execution.

We offer:

• Newly fitted dedicated site in Whittlesford near Cambridge – on-site parking and regular trains to Cambridge, London and Norwich
• Employee share option plan
• Private health insurance
• Pension plan (matching up to 8%)
• Collaborative and pioneering environment, at the leading edge of synthetic genomics and engineered translation

We want to build a team with trust and respect for each other and create a culture of collaboration, openness, curiosity, and scientific excellence.

We are built on three principles:

• We imagine: We think big and plan our own path for success.
• We pioneer: We take action and grow together as one to break moulds.
• We deliver: We take ownership and work together to deliver excellence.

Constructive Bio is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.