Senior Full Stack Engineer | Biotechnology | Protein | Python | Typescript | React | London, Hybrid

Enigma; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Competitive pay

Health insurance

Pension/401(k)

Generous leave

Travel

Job summary

Enigma, a London-based biotech company, is seeking a Senior Full Stack Engineer to own the software powering frontier generative models and production workflows. You will build APIs, data pipelines, and frontends used by researchers in wet labs to accelerate protein design and validation.

You’ll work with ML researchers, biologists, and product teams in a hybrid setup, delivering robust, observable systems on cloud infrastructure while maintaining fast iteration cycles in a cutting-edge biology

Qualifications

• Own production full-stack APIs, services and UIs from concept to production.
• Build performant ML-adjacent data pipelines and deploy models.
• Collaborate with ML researchers, biologists and product teams to translate biology constraints into software.
• Design observability and benchmarks to monitor model performance, latency and cost.

Responsibilities

• Ship production-grade APIs, services, and UIs for proprietary generative models.
• Build and scale data pipelines ingesting wet-lab results and feeding experiments back into models.
• Own end-to-end features from prototype to production on cloud accelerators.
• Design benchmarks and observability for model performance and cost visibility.
• Partner with ML researchers, protein designers, and biologists to translate lab constraints into software.

Skills

Production full-stack ownership

Cloud training/inference

Data pipelines

Collaborative cross-functional work

Job description

Senior Full Stack Engineer | Biotechnology | Protein | Python | Typescript | React | London, Hybrid

A leading Biotechnology startup are making biology programmable so we can transform health and sustainability. Their team co-developed AlphaFold, invented latent diffusion, and built high-throughput protein platforms. You will own the software that turns frontier generative models into reliable, production systems scientists and partners actually use—so designed proteins reach the wet lab faster and work in the real world.

Performance Objectives

• Ship production-grade APIs, services, and UIs that serve proprietary generative models with high reliability, so protein designers and partners can run inference against biological targets within weeks of joining.
• Build and scale data pipelines that ingest wet-lab results, construct training/eval splits, and feed experimental outcomes back into models, measurably lifting design success rates across campaign rounds.
• Own end-to-end features from prototype to production: robust, tested, reviewed code that runs training and inference on cloud accelerators and stays maintainable in a shared research-engineering codebase.
• Design informative benchmarks and observability so model performance, latency, and cost are visible to ML scientists, biologists, and leadership.
• Partner with ML researchers, protein designers, and biologists to translate lab constraints into software, closing the loop between generation and experimental validation.
• Raise engineering standards (CI, reviews, infra) so a small interdisciplinary team can move urgently without sacrificing scientific rigor.

You join a 30 person, for-profit team across San Francisco and London (hybrid, offsites for trust). You report into engineering/platform, work in a joint codebase with ML scientists and protein designers, and use cloud accelerators, modern version control, and lab data systems. Competitive pay, health insurance, pension/401(k), generous leave (including parental), and travel.

Essential Qualifications

• Proven delivery of production full-stack systems (APIs, data pipelines, frontends) that other teams depend on, with ownership from conception to completion.
• Strong software craft: robust, tested, reviewed code; fast prototyping that also meets production quality; cloud training/inference and distributed data/models.
• Experience building performant ML-adjacent data pipelines and serving large models.
• Ability to thrive in a fast, ambiguous biotech environment and collaborate across ML, biology, and product.
• Mission-driven curiosity: you care about patients and the planet and will learn enough protein/cell biology to make software decisions that matter in the lab.

Role Selling Points

• Work with people who built AlphaFold and latent diffusion on a moonshot to program biology.
• Your code directly enables proteins that are tested in wet lab and, ultimately, therapies and sustainability applications.
• Interdisciplinary culture, scientific excellence, and the chance to shape a young company’s platform as we grow.
• Hybrid work, competitive package, and a team that values diverse backgrounds and continuous learning.

Senior Full Stack Engineer | Biotechnology | Protein | Python | Typescript | React | London, Hybrid