Machine Learning Research Engineer in Peterborough
Machine Learning Research Engineer

Machine Learning Research Engineer in Peterborough

Peterborough Full-Time 50000 - 70000 £ / year (est.) No home office possible
Constructive Bio

At a Glance

  • Tasks: Develop and implement cutting-edge ML models for biological applications.
  • Company: Join a pioneering biotech startup transforming living cells into biofactories.
  • Benefits: Competitive salary, employee share options, private health insurance, and pension plan.
  • Why this job: Make a real impact at the intersection of ML and experimental biology.
  • Qualifications: BSc or MSc in engineering with ML experience; strong communication skills required.
  • Other info: Collaborative culture focused on innovation and scientific excellence.

The predicted salary is between 50000 - 70000 £ per year.

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. We recently secured $58 million Series A fundraising.

What we’re looking for:

We are looking for an ML engineer who can turn prototypes into production systems and work fluidly across the biology-ML boundary. You will 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 will 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 are 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 are a small, focused team building toward a programmable biomolecules platform. As an early joiner, you will have genuine influence over technical direction, not just execution of a pre-set roadmap. You will 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 will 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 will 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.

Machine Learning Research Engineer in Peterborough employer: Constructive Bio

Constructive Bio is an exceptional employer, offering a unique opportunity to work at the forefront of biotechnology in Whittlesford, Cambridge. With a collaborative and pioneering work culture, employees are empowered to influence technical direction and engage deeply with both machine learning and experimental biology. The company provides excellent benefits, including a share option plan, private health insurance, and a pension scheme, all within a supportive environment that values trust, respect, and scientific excellence.
Constructive Bio

Contact Detail:

Constructive Bio Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Research Engineer in Peterborough

✨Tip Number 1

Network like a pro! Reach out to people in the industry, especially those connected to Constructive Bio. Attend relevant meetups or conferences and don’t be shy about introducing yourself. You never know who might have a lead on your dream job!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and biology. This is your chance to demonstrate how you can turn prototypes into production systems. Make it easy for potential employers to see what you can do!

✨Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with PyTorch and Hugging Face, and how you can bridge the gap between ML and biology. Practice explaining complex concepts in simple terms!

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Constructive Bio. Don’t forget to tailor your application to highlight your passion for both ML and biology!

We think you need these skills to ace Machine Learning Research Engineer in Peterborough

Machine Learning
PyTorch
Hugging Face
Algorithms
Data Structures
Software Design Principles
Communication Skills
Computational Biology
Genomic Language Models
Experimentation Infrastructure
Model Fine-Tuning
Cross-Functional Collaboration
Code Documentation
Technical Problem-Solving

Some tips for your application 🫡

Show Your Passion for ML and Biology: When you're writing your application, let your enthusiasm for machine learning and biology shine through. We want to see how you connect the dots between these fields and why you're excited about the role at Constructive Bio.

Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this specific role. Highlight your experience with PyTorch, Hugging Face, and any relevant projects that showcase your skills in ML and computational biology. We love seeing how your background fits with our mission!

Be Clear and Concise: Keep your application clear and to the point. Use straightforward language to explain your technical skills and experiences. Remember, we appreciate strong communication skills, so make it easy for us to understand your qualifications.

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. Plus, it shows you’re serious about joining our team at Constructive Bio.

How to prepare for a job interview at Constructive Bio

✨Know Your ML Models

Make sure you’re well-versed in the state-of-the-art sequence models mentioned in the job description, like transformers and diffusion models. Be ready to discuss your hands-on experience with these technologies and how you've applied them in real-world scenarios.

✨Show Your Collaborative Spirit

Since this role involves working closely with experimental biologists, highlight any past experiences where you’ve successfully collaborated across disciplines. Prepare examples that showcase your ability to communicate complex technical concepts to non-ML professionals.

✨Demonstrate Your Curiosity About Biology

Constructive Bio values a genuine interest in biology. Brush up on relevant biological concepts and be prepared to discuss how your ML expertise can contribute to biological research. Showing enthusiasm for the field can set you apart from other candidates.

✨Prepare for Technical Challenges

Expect to face technical questions or challenges during the interview. Practice coding problems related to algorithms and data structures, and be ready to explain your thought process. This will demonstrate your problem-solving skills and your ability to write clean, maintainable code.

Machine Learning Research Engineer in Peterborough
Constructive Bio
Location: Peterborough

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