What We're Looking For We are seeking a Lab Automation Engineer to build the software and systems infrastructure that turns our physical lab into a fully autonomous system. You will design and implement software drivers for different scientific instruments as well as the orchestration layer that connects instruments, robots and data pipelines into an continuous experimental workflow. You will be joining a small, highly ambitious team of world-renowned engineers, AI researchers, and materials scientists. We move fast and value people who are energised by that. This is a role for someone who is at home in both a codebase and a lab, who has felt the frustration of poorly automated instruments and done something about it, and who is excited to build a first of its kind autonomous lab. What You'll Do Design and implement the orchestration layer that coordinates instruments, robotic handling, and data capture across our automated lab. Write and maintain software drivers for scientific instruments, handling vendor APIs, serial protocols, and communication standards. Automate experimental workflows that integrate robotics, instrument control and real time data analysis. Leverage open source lab automation frameworks (MADSci or equivalent) to fit our specific instrument suite and research needs. Work directly with materials scientists and ML researchers to translate experimental protocols into reliable, reproducible automated pipelines. Maintain and improve the reliability of running automated workflows, including error handling, logging, and recovery from instrument failures. Evaluate and integrate new instruments and robotic systems as our lab capabilities expand. Skills & Qualifications Proven experience building automation systems for scientific laboratories, either in industry or at a research institution. Strong Python skills; comfortable building production quality software. Direct experience writing software drivers or integrations for scientific instruments, and an understanding of the challenges involved: inconsistent vendor documentation, brittle communication protocols, hardware edge cases. Experience with lab orchestration frameworks such as MADSci or similar open source or commercial systems. Enough hardware fluency to diagnose whether a problem is in the software, the instrument, or the integration between them. Experience designing automated workflows end to end: from sample handling through measurement, data capture, and handoff to downstream analysis. Comfortable working in a lab environment and collaborating closely with scientists who are not software engineers. Nice to Have Background in materials science, chemistry, metallurgy, or a related physical science discipline. Experience integrating robotic sample handling (liquid handlers, robotic arms, plate movers) into automated workflows. Contributions to open source lab automation projects. Experience at a national laboratory (Argonne, Diamond, ISIS, or similar) or an automated biotech or material science platform company. Why Join Us Build the automation infrastructure for one of the most ambitious materials discovery programmes in the world. Work at the frontier of autonomous labs, where your software directly shapes what science gets done. Collaborate with world class researchers across materials science and AI. Diffractive is building the AI Material Scientist that autonomously learns from real world experimentation to push the boundaries of scientific discovery. We're early, moving fast, and working on problems that genuinely matter. You'll join a small, high calibre team where your work has real impact from day one. We're London based with a flexible approach to how and where you work. We offer competitive salary, generous equity and benefits. You'll have a real stake in what you build and in the company's overall success. How to Apply If you're excited about this role and believe you could thrive in it, we'd encourage you to apply even if you may not align with every part of the job description. Diffractive is an equal opportunities employer. We are committed to creating an inclusive environment for all employees and welcome applications from people of all backgrounds, experiences, and identities. If you require any adjustments or accommodations at any point during the interview process please let us know - we will be happy to help. Hit the apply button below to submit your application. We are looking forward to hearing from you!
11/07/2026
Full time
What We're Looking For We are seeking a Lab Automation Engineer to build the software and systems infrastructure that turns our physical lab into a fully autonomous system. You will design and implement software drivers for different scientific instruments as well as the orchestration layer that connects instruments, robots and data pipelines into an continuous experimental workflow. You will be joining a small, highly ambitious team of world-renowned engineers, AI researchers, and materials scientists. We move fast and value people who are energised by that. This is a role for someone who is at home in both a codebase and a lab, who has felt the frustration of poorly automated instruments and done something about it, and who is excited to build a first of its kind autonomous lab. What You'll Do Design and implement the orchestration layer that coordinates instruments, robotic handling, and data capture across our automated lab. Write and maintain software drivers for scientific instruments, handling vendor APIs, serial protocols, and communication standards. Automate experimental workflows that integrate robotics, instrument control and real time data analysis. Leverage open source lab automation frameworks (MADSci or equivalent) to fit our specific instrument suite and research needs. Work directly with materials scientists and ML researchers to translate experimental protocols into reliable, reproducible automated pipelines. Maintain and improve the reliability of running automated workflows, including error handling, logging, and recovery from instrument failures. Evaluate and integrate new instruments and robotic systems as our lab capabilities expand. Skills & Qualifications Proven experience building automation systems for scientific laboratories, either in industry or at a research institution. Strong Python skills; comfortable building production quality software. Direct experience writing software drivers or integrations for scientific instruments, and an understanding of the challenges involved: inconsistent vendor documentation, brittle communication protocols, hardware edge cases. Experience with lab orchestration frameworks such as MADSci or similar open source or commercial systems. Enough hardware fluency to diagnose whether a problem is in the software, the instrument, or the integration between them. Experience designing automated workflows end to end: from sample handling through measurement, data capture, and handoff to downstream analysis. Comfortable working in a lab environment and collaborating closely with scientists who are not software engineers. Nice to Have Background in materials science, chemistry, metallurgy, or a related physical science discipline. Experience integrating robotic sample handling (liquid handlers, robotic arms, plate movers) into automated workflows. Contributions to open source lab automation projects. Experience at a national laboratory (Argonne, Diamond, ISIS, or similar) or an automated biotech or material science platform company. Why Join Us Build the automation infrastructure for one of the most ambitious materials discovery programmes in the world. Work at the frontier of autonomous labs, where your software directly shapes what science gets done. Collaborate with world class researchers across materials science and AI. Diffractive is building the AI Material Scientist that autonomously learns from real world experimentation to push the boundaries of scientific discovery. We're early, moving fast, and working on problems that genuinely matter. You'll join a small, high calibre team where your work has real impact from day one. We're London based with a flexible approach to how and where you work. We offer competitive salary, generous equity and benefits. You'll have a real stake in what you build and in the company's overall success. How to Apply If you're excited about this role and believe you could thrive in it, we'd encourage you to apply even if you may not align with every part of the job description. Diffractive is an equal opportunities employer. We are committed to creating an inclusive environment for all employees and welcome applications from people of all backgrounds, experiences, and identities. If you require any adjustments or accommodations at any point during the interview process please let us know - we will be happy to help. Hit the apply button below to submit your application. We are looking forward to hearing from you!
What We're Looking For We are seeking a DevOps Engineer to build and own the infrastructure that underpins our AI driven materials discovery platform. You'll work directly with world renowned ML researchers and software engineers to accelerate real scientific breakthroughs by making model training, experimentation, and deployment fast, reliable, and reproducible. This is a foundational hire. You'll set the patterns others build on. You will be joining a small, highly ambitious team of world renowned engineers, AI researchers, and materials scientists. We move fast and value people who are energised by that. What You'll Do Design, provision, and manage cloud infrastructure (AWS/GCP) using infrastructure as code; Terraform, Pulumi, or equivalent. Own GPU compute environments for model training and inference, including cluster configuration, job scheduling, and cost optimisation. Build and maintain CI/CD pipelines that support rapid model iteration, automated testing, and safe deployments. Support ML workflow orchestration; experiment tracking, training run management, and data pipeline reliability. Ensure reproducibility across research and production environments through containerisation and rigorous environment management. Define monitoring, alerting, and incident response processes so the team can move fast without things silently breaking. Implement security best practices: secrets management, IAM, network segmentation, vulnerability scanning. Build internal tooling and documentation that lets researchers self serve infrastructure without waiting on you. Skills & Qualifications 4+ years in a DevOps, Platform Engineering, or SRE role. Strong proficiency with at least one major cloud provider and its core services (compute, storage, networking, IAM). Hands on experience with infrastructure as code and container orchestration (Kubernetes or equivalent). Solid CI/CD pipeline experience, GitHub Actions, GitLab CI, or similar. Proficient in Python and Bash; comfortable reading and writing code across a polyglot stack. Deep Linux systems knowledge and strong networking fundamentals. A bias for building things properly the first time, even under early stage constraints. Nice to Have Experience with GPU cluster management and ML training workloads (NVIDIA, CUDA, distributed training). Familiarity with MLOps tooling: Experiment tracking (MLflow, Weights & Biases). Workflow orchestration (Airflow, Prefect, Argo). Data versioning (DVC). Background in scientific computing or HPC environments. Prior experience at a deep tech or computational science company. Why Join Us Work directly on infrastructure that enables AI to make real scientific discoveries. Shape how we build from day one, no legacy systems, no inherited mess. Collaborate with world class researchers across materials science and machine learning. Diffractive is building the AI Material Scientist that autonomously learns from real world experimentation to push the boundaries of scientific discovery. We're early, moving fast, and working on problems that genuinely matter. We are a London based company with a flexible approach to how and where you work. We offer competitive salary, generous equity, and benefits. You'll have a real stake in what you build and in the company's overall success. Equal Opportunity Diffractive is an equal opportunities employer. We are committed to creating an inclusive environment for all employees and welcome applications from people of all backgrounds, experiences, and identities. If you require any adjustments or accommodations at any point during the interview process please let us know - we will be happy to help.
11/07/2026
Full time
What We're Looking For We are seeking a DevOps Engineer to build and own the infrastructure that underpins our AI driven materials discovery platform. You'll work directly with world renowned ML researchers and software engineers to accelerate real scientific breakthroughs by making model training, experimentation, and deployment fast, reliable, and reproducible. This is a foundational hire. You'll set the patterns others build on. You will be joining a small, highly ambitious team of world renowned engineers, AI researchers, and materials scientists. We move fast and value people who are energised by that. What You'll Do Design, provision, and manage cloud infrastructure (AWS/GCP) using infrastructure as code; Terraform, Pulumi, or equivalent. Own GPU compute environments for model training and inference, including cluster configuration, job scheduling, and cost optimisation. Build and maintain CI/CD pipelines that support rapid model iteration, automated testing, and safe deployments. Support ML workflow orchestration; experiment tracking, training run management, and data pipeline reliability. Ensure reproducibility across research and production environments through containerisation and rigorous environment management. Define monitoring, alerting, and incident response processes so the team can move fast without things silently breaking. Implement security best practices: secrets management, IAM, network segmentation, vulnerability scanning. Build internal tooling and documentation that lets researchers self serve infrastructure without waiting on you. Skills & Qualifications 4+ years in a DevOps, Platform Engineering, or SRE role. Strong proficiency with at least one major cloud provider and its core services (compute, storage, networking, IAM). Hands on experience with infrastructure as code and container orchestration (Kubernetes or equivalent). Solid CI/CD pipeline experience, GitHub Actions, GitLab CI, or similar. Proficient in Python and Bash; comfortable reading and writing code across a polyglot stack. Deep Linux systems knowledge and strong networking fundamentals. A bias for building things properly the first time, even under early stage constraints. Nice to Have Experience with GPU cluster management and ML training workloads (NVIDIA, CUDA, distributed training). Familiarity with MLOps tooling: Experiment tracking (MLflow, Weights & Biases). Workflow orchestration (Airflow, Prefect, Argo). Data versioning (DVC). Background in scientific computing or HPC environments. Prior experience at a deep tech or computational science company. Why Join Us Work directly on infrastructure that enables AI to make real scientific discoveries. Shape how we build from day one, no legacy systems, no inherited mess. Collaborate with world class researchers across materials science and machine learning. Diffractive is building the AI Material Scientist that autonomously learns from real world experimentation to push the boundaries of scientific discovery. We're early, moving fast, and working on problems that genuinely matter. We are a London based company with a flexible approach to how and where you work. We offer competitive salary, generous equity, and benefits. You'll have a real stake in what you build and in the company's overall success. Equal Opportunity Diffractive is an equal opportunities employer. We are committed to creating an inclusive environment for all employees and welcome applications from people of all backgrounds, experiences, and identities. If you require any adjustments or accommodations at any point during the interview process please let us know - we will be happy to help.
Diffractive Labs in London is looking for a DevOps Engineer to build and manage cloud infrastructure for their AI-driven materials discovery platform. You will work closely with top researchers and engineers to facilitate scientific breakthroughs. Responsibilities include designing cloud solutions, maintaining CI/CD pipelines, and ensuring infrastructure reliability. Applicants should have 4+ years of relevant experience and proficiency in cloud technologies. The company offers competitive salaries and equity options while fostering an inclusive work environment.
11/07/2026
Full time
Diffractive Labs in London is looking for a DevOps Engineer to build and manage cloud infrastructure for their AI-driven materials discovery platform. You will work closely with top researchers and engineers to facilitate scientific breakthroughs. Responsibilities include designing cloud solutions, maintaining CI/CD pipelines, and ensuring infrastructure reliability. Applicants should have 4+ years of relevant experience and proficiency in cloud technologies. The company offers competitive salaries and equity options while fostering an inclusive work environment.