Forward Deployed AI Engineer in City of London

Forward Deployed AI Engineer in City of London

City of London Full-Time 72000 - 88000 £ / year (est.) Hybrid
Latent Labs

At a Glance

  • Tasks: Deploy and optimise AI models for biotech customers, ensuring seamless integration into their workflows.
  • Company: Join Latent Labs, a pioneering tech company at the forefront of generative biology.
  • Benefits: Enjoy competitive pay, private health insurance, generous leave, and hybrid working options.
  • Other info: Dynamic environment with opportunities for growth and interdisciplinary collaboration.
  • Why this job: Make a real-world impact in drug discovery while collaborating with top minds in AI and biology.
  • Qualifications: Degree in Computer Science or Machine Learning; experience in deploying AI systems is essential.

The predicted salary is between 72000 - 88000 £ per year.

We are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering.

You will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams.

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. Team offsites 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.

You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks. You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models.

You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work. You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.

You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations. You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements.

What sets you apart:

  • You have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling.
  • You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features.
  • You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system.
  • You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations.

Your responsibilities:

  • Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure.
  • Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements.
  • Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.
  • Ensure deployments meet enterprise standards for security, performance and reliability.

Customer advocacy & product feedback:

  • Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as needed.
  • Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.
  • Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings.
  • Create technical documentation, integration guides and best-practice resources for customers.

Self development:

  • Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling.
  • Gain a strong working understanding of protein and cell biology as it relates to our product.
  • Participate in knowledge sharing, e.g. organise and present at our internal reading group.

We offer strongly competitive compensation and benefits packages, including private health insurance, pension 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.

Forward Deployed AI Engineer in City of London employer: Latent Labs

At Latent Labs, we pride ourselves on being an exceptional employer, offering a dynamic work environment where innovation meets scientific excellence. Our commitment to employee growth is reflected in our strong mentorship culture and opportunities for collaboration with leading experts in AI and biology. With competitive compensation, comprehensive benefits, and a focus on diversity and inclusion, we ensure that every team member feels valued and empowered to contribute to groundbreaking advancements in the pharmaceutical and biotech sectors.

Latent Labs

Contact Details:

Latent Labs Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Forward Deployed AI Engineer in City of London

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Latent Labs or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Latent Labs.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Latent Labs.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Latent Labs that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Forward Deployed AI Engineer in City of London

Machine Learning
Software Engineering Principles
API Development
Infrastructure Design
Cloud Infrastructure (AWS, GCP, Azure)
Containerisation (Docker, Kubernetes)
CI/CD Pipelines

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Latent Labs.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Latent Labs and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Latent Labs

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Latent Labs uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.