At a Glance
- Tasks: Manage high-performance computing and implement scalable ML solutions.
- Company: Latent Labs, pioneers in generative AI and biology.
- Benefits: Competitive pay, private health insurance, generous leave, and hybrid work options.
- Other info: Dynamic environment with opportunities for travel and professional growth.
- Why this job: Join a mission-driven team tackling complex challenges in synthetic biology.
- Qualifications: Experience with Kubernetes, cloud platforms, and ML frameworks like PyTorch.
The predicted salary is between 60000 - 80000 £ per year.
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. 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.
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
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.
Member of Technical Staff - ML Engineering in London employer: Latent Labs
At Latent Labs, we pride ourselves on being an exceptional employer, offering a stimulating work environment where innovation thrives. Our commitment to scientific excellence is matched by our dedication to employee growth, providing opportunities for continuous learning and collaboration within an interdisciplinary team. With competitive compensation, generous leave policies, and a culture that values diverse perspectives, joining us means contributing to groundbreaking advancements in synthetic biology while enjoying a supportive and dynamic workplace in London.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff - ML Engineering in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Latent Labs. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got projects or contributions related to ML engineering, make sure to highlight them in conversations. We love seeing real-world applications of your expertise.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Kubernetes and cloud platform knowledge. We want to see how you tackle problems, so practice explaining your thought process clearly.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you're genuinely interested in joining our mission at Latent Labs.
We think you need these skills to ace Member of Technical Staff - ML Engineering in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Kubernetes, cloud platforms, and ML engineering. We want to see how your skills align with our needs, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re passionate about machine learning and biology. Share your journey, your motivations, and how you can contribute to our moonshot mission at Latent Labs.
Showcase Your Projects:If you've worked on any interesting projects related to generative models or HPC frameworks, make sure to include them! We love seeing practical applications of your skills and how you tackle complex challenges.
Apply Through Our Website:We encourage you to apply directly 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 us you’re keen to join our team!
How to prepare for a job interview at Latent Labs
✨Know Your Tech Inside Out
Make sure you’re well-versed in Kubernetes, cloud platforms, and HPC frameworks. Brush up on your knowledge of PyTorch and distributed computing, as these are crucial for the role. Being able to discuss your hands-on experience with these technologies will show that you're not just familiar but truly capable.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially those related to deploying and optimising ML models. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for the interviewers to see how you tackle complex problems.
✨Demonstrate Your Collaborative Spirit
Since the team values interdisciplinary exchange, be ready to share examples of how you've successfully collaborated with others in the past. Highlight any experiences working with diverse teams, particularly in machine learning or biology, to show that you can thrive in their collaborative environment.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s projects, culture, and future goals. This not only shows your genuine interest in the role but also helps you gauge if the company aligns with your own values and career aspirations. Asking about their approach to innovation in synthetic biology could be a great conversation starter!
