Software Engineer (Scheduler), London New London

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery. Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture.

About Iso

Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.

Your Impact

You will join our newly formed Scheduling team to own and extend the systems that orchestrate compute allocation to complex machine learning workloads running on Kubernetes. You will be responsible for optimizing our compute footprint, ensuring that dynamic batch inference and large-scale training runs are scheduled reliably and efficiently. We are looking for an engineer who operates comfortably at the intersection of distributed systems and modern ML infrastructure. You will design systems that support large-scale, topology-sensitive workloads, optimize batch queuing frameworks and write custom Kubernetes controllers. Your work will directly determine our ability to maximize hardware utilization and accelerate the pace of AI-driven drug discovery.

What you will do

• Own the Scheduling Layer: Design, operate, and extend ML workload scheduling systems to handle dynamic batch inference and long-running training workloads.
• Optimize Compute Utilization: Drive the implementation of scheduling policies like gang scheduling, topology-aware placement, and preemption to ensure efficient use across our fleets of committed GPUs and TPUs.
• Partner with Research: Collaborate directly with ML researchers and the broader Infrastructure team to understand workload behavior, troubleshoot bottlenecks, and turn research requirements into platform capabilities.
• Ensure Reliability: Build systems with clear failure semantics. Participate in the operational lifecycle of the scheduling ecosystem, designing robust processes, runbooks, and SLOs to maintain high availability.
• Build Custom Infrastructure: Build and maintain custom Kubernetes controllers, operators, and CRDs that adapt the cluster orchestration layer to the specific requirements of our ML pipelines.
• Scheduling Frameworks: Practical experience building or operating cluster schedulers, batch systems, or queuing frameworks (e.g., Kueue, Volcano, Slurm).
• Deep Kubernetes Expertise: Deep, hands‑on Kubernetes experience, moving beyond standard usage to write and maintain custom K8s controllers, operators, or interacting directly with cluster orchestration APIs.
• Cloud Infrastructure Experience: Strong practical experience with cloud providers, focusing on compute provisioning, networking, and Infrastructure as Code to build scalable foundational environments.
• Adaptability: A solid foundation in DevOps/SRE best practices, with the ability to adapt these principles to the dynamic nature of AI accelerator infrastructure.
• Programming Proficiency: Strong programming skills, with high proficiency in Python or Go.

Preferred qualifications

• Familiarity with ML infrastructure nuances: Nvidia GPUs, Google TPUs, gang scheduling, or collective networking.
• Previous experience in High-Performance Computing or maximizing utilization in environments with fixed/committed hardware constraints.
• Familiarity with GCP cloud compute infrastructure and Infrastructure as Code.
• Background in ML SWE or infrastructure SRE work supporting machine learning research activities.

Culture and values

• Thoughtful: Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day.
• Brave: Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.
• Determined: Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we.
• Together: Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.

Creating an extraordinary company

We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact.

We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.

Please note that when you submit an application, your data will be processed in line with our privacy policy.

As an AI‑first company, we embrace tools like Gemini. However, our interview process is designed to understand your unique expertise and problem-solving skills, as well as what motivates you. Therefore, we ask that you refrain from using any AI tools, transcription services, or other assistants during your interview and assessment process, unless you've made prior arrangements with our Talent team for specific needs or accommodations. (If you require any adjustments, please discuss this with the Talent team during your initial screening call.)