Software Engineer (Scheduler), London
Isomorphic Labs is hiring a Software Engineer (Scheduler), London (United Kingdom). Level rates it ; you can apply on Isomorphic Labs.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- The posting mentions AI research among its tools and skills.
- Isomorphic Labs has 32 other open roles on Level.
- Posted in the last few days.
AI in this role
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.
The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you.
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.
Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.
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.
Minimum qualifications
- 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. Strong familiarity with K8s scheduler.
- 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
- Experience operating Kueue.
- 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
We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.
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.
Hybrid working
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.
How we rate this
Software Engineer (Scheduler), London at Isomorphic Labs rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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