Jobs at Isomorphic Labs

Design, operate, and extend scheduling systems for large-scale machine learning workloads on Kubernetes. Optimize GPU and TPU utilization through gang scheduling, topology-aware placement, and preemption. Build custom Kubernetes controllers, operators, and CRDs; ensure reliability through operational processes, runbooks, and SLOs; and collaborate with ML researchers and infrastructure teams to support efficient batch inference and training.

Lead the Platform group in designing, operating, and improving cloud infrastructure for research, development, production, and machine-learning training and inference. Own Kubernetes, infrastructure as code, deployment tooling, monitoring, automation, software lifecycle practices, and architectural decisions. Collaborate with engineers, scientists, ML researchers, product, business development, and operations teams to deliver reliable infrastructure in a fast-moving environment.

Leads corporate development and inorganic growth initiatives across digital biology, biotechnology, and enabling technologies. Responsibilities include market landscaping, scientific and commercial opportunity evaluation, business case development, valuation modeling, deal structuring, negotiation, due diligence, transaction closing, strategic investments, executive recommendations, pipeline governance, and cross-functional coordination with R&D, machine learning, legal, finance, and commercial teams.

Build and evolve large-scale machine learning infrastructure for distributed training and inference workloads. The role involves improving platform reliability, deploying research-supporting agents, enabling scalable ML development, and partnering with engineering, research, and product teams. Strong Python and large-scale infrastructure experience are essential; Kubernetes, GCP, internal platform development, and multi-cloud experience are advantageous. The position follows a hybrid model requiring three office days per week in London.

Design and operate large-scale compute infrastructure for AI and machine learning workloads. Build observability and telemetry systems, improve GPU efficiency and workload goodput, integrate accelerator hardware, maintain Kubernetes and cloud clusters, and develop automated recovery and reliability mechanisms. Collaborate with ML infrastructure, research, platform, and business teams while contributing to architectural and tooling decisions.

Architects and builds secure, scalable LLM systems and agentic infrastructure for scientific and business workflows. Responsibilities include model serving, observability, governance, cost management, context management, tool use, RAG, evaluation frameworks, IDE integrations, fine-tuning support, and collaboration with researchers and business stakeholders. The role requires production-grade Python, cloud system design, LLM internals expertise, and experience with probabilistic ML systems.

Operating Partner supporting AI leadership by advising executives, prioritizing strategic initiatives, coordinating cross-functional teams, translating complex technical topics into executive communications, driving execution, and improving organizational efficiency. The role partners across research, engineering, product, and operations to deliver high-priority initiatives and support organizational scaling.

Senior Legal Counsel supporting complex corporate, business development, and strategic transactions, including research collaborations, co-development agreements, M&A, investments, and data and IP licensing. Responsibilities include structuring and negotiating deals, leading legal and IP due diligence, mitigating data governance and technology-transfer risks, creating deal playbooks and term sheets, improving legal operations, and advising business development, scientific, and leadership teams.

Own the end-to-end candidate experience, including complex global interview scheduling, candidate communications, onsite or virtual interview hosting, ATS data integrity, onboarding compliance, feedback analysis, and process improvement. The role partners with hiring managers and talent leaders, documents and scales recruiting workflows, supports training, and uses data and AI to improve talent acquisition operations.

The Principal Software Engineer will ensure the reliability and scalability of AI systems, leading infrastructure improvements and optimizing ML workflows.

Research Engineer responsible for optimizing large language model post-training and scaling frontier models for drug discovery. The role involves distributed training and inference performance optimization, fine-tuning and reinforcement learning framework evaluation, bottleneck diagnosis, production system deployment, and low-precision methods. The engineer will collaborate with research and engineering teams across machine learning, computational biology, and chemistry.

Design and develop novel machine learning models and training algorithms for drug discovery. Lead and run research projects, implement and scale training/inference frameworks, analyze experiments, and collaborate across disciplines. Mentor and provide technical guidance to other ML researchers and contribute to research direction and presentations.

As a Research Engineer, you will develop and optimize AI models for drug discovery, collaborating with scientists to advance ML applications in biopharmaceuticals.

Leads multi-quarter information security roadmaps and complex security initiatives across cloud security, IAM, Secure SDLC, regulated data transfers, and agentic AI workflows. Partners with engineering, machine learning, research, and business teams to deliver security programs, manage risk and dependencies, advocate for InfoSec capabilities, and provide CISO-level visibility through automated dashboards and operational metrics.

Operate and secure self-hosted multi-user vendor applications: deploy and maintain Kubernetes-based instances, build CI/CD pipelines and IaC, integrate SSO/RBAC, run vulnerability scanning and remediation, automate rollouts across endpoints, and manage monitoring, backups, and low-downtime upgrades.

As a Research Scientist focused on Large Language Models, you'll develop and apply advanced ML techniques in drug discovery, contributing to groundbreaking research and leading projects in a collaborative environment.

Isomorphic Labs seeks to recruit interested candidates for roles in software engineering, machine learning research, computational chemistry, and project management for future openings.