Technical Staff Member – Applied AI
Latent Labs
full-time
Posted on:
Location Type: Hybrid
Location: London • United Kingdom
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Job Level
Tech Stack
About the role
- Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.
- Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
- Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.
- Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.
- Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.
- Ensure deployments meet customer standards for security, performance and reliability.
- Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.
- Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.
- In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.
- Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.
- Create technical documentation, integration guides and best-practice resources.
- Spend time working on-site at international partner locations as needed.
Requirements
- You are a strong ML researcher with experience in generative modelling.
- You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues.
- You have a deep understanding of generative model architectures, training dynamics and inference behaviour.
- You are a skilful ML developer.
- You write ML code that is robust, tested and easy to maintain.
- You have experience using version control and code review systems.
- You are a fast prototyper and hacker who can also write beautiful production code.
- You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.
- You are customer-facing and delivery-oriented.
- You thrive in environments where customer success is the primary measure of your work.
- You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.
- You are passionate about model performance.
- You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed.
- You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.
- You are mission driven and curious.
Benefits
- Private health insurance
- Pension contributions
- Generous leave policies (including gender neutral parental leave)
- Hybrid working
- Travel opportunities and more
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
generative modelingmachine learningML data pipelinesAPI integrationsmodel-serving infrastructuremodel inferencetraining dynamicsinference behaviourversion controlproduction code
Soft Skills
collaborationcustomer-facingdelivery-orientedcommunicationproblem-solvingrelationship buildingadaptabilitycuriosityscientific rigortechnical documentation