Member of Technical Staff & ML Engineering

the Homebase; Greater London; Hybrid; GBP 60,000 - GBP 80,000; Full time

Job summary

A leading lab in synthetic biology is seeking a machine learning research engineer to manage high performance computing and model serving initiatives. The ideal candidate has extensive experience with Kubernetes, major cloud platforms, and production engineering. Responsibilities include deploying and optimizing compute clusters and designing ML solutions. This position offers competitive compensation, health insurance, generous leave policies, and a hybrid working environment, fostering innovation in synthetic biology.

Benefits

Private health insurance

Pension/401(K) contributions

Generous leave policies

Hybrid working

Travel opportunities

Qualifications

• Extensive experience in machine learning and model deployment.
• Strong background in managing high-performance computing environments.
• Ability to develop dynamic compute solutions.

Responsibilities

• Deploy, maintain, and optimize production and research compute clusters.
• Design and implement scalable ML inference solutions.
• Contribute to productizing model APIs for external use.

Skills

Deep experience with Kubernetes and containerized workflows

Experience with major cloud platforms (AWS, GCP, Azure)

Knowledge of DevOps and related tools (Terraform, etc)

Knowledge of HPC frameworks (Slurm, Ray, etc)

Production engineering & reliability experience

PyTorch & distributed computing experience

Job description

The opportunity

We are looking for a highly skilled machine learning research engineer with significant experience in training and implementing large scale generative models. In this role you will manage our high performance computing environment, and our model serving initiatives. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases

Who we are

At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.

Our team is committed to interdisciplinary exchange, continuous learning and collaboration.sites help us foster a culture of trust across our London and San Francisco sites.

We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.

Who you are

• Deep experience with Kubernetes and containerized workflows
• Experience with major cloud platforms (AWS, GCP, Azure)
• Knowledge of DevOps and related tools (Terraform, etc)
• Knowledge of HPC frameworks (Slurm, Ray, etc)
• Production engineering & reliability experience
• PyTorch & distributed computing experience

Your Responsibilities

• Deploy, maintain, and optimize production and research compute clusters
• Design and implement scalable and efficient ML inference solutions
• Develop dynamic / heterogeneous compute solutions for balancing research and production needs
• Contribute to productizing model APIs for external use
• Develop infrastructure observability and monitoring solutions

Apply

We offer strongly competitive compensation and benefits packages, including:

• Private health insurance
• Pension/401(K) contributions
• Generous leave policies (including gender neutral parental leave)
• Hybrid working
• Travel opportunities and more

We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.

We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.