At a Glance
- Tasks: Lead the reliability of AI systems to revolutionise drug discovery and healthcare.
- Company: Join IsoLabs, a pioneering biotech firm transforming health with AI.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative culture focused on curiosity, creativity, and making a difference.
- Why this job: Make a real impact on global health by advancing cutting-edge AI technology.
- Qualifications: Experience in managing large-scale AI workloads and cloud infrastructure.
The predicted salary is between 70000 - 90000 £ per year.
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 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: We are building the largest foundation models in biotech and applying them immediately to cure disease. You will play a pivotal role in ensuring the reliability and scalability of the foundations that make this possible. As a Principal Engineer, you will lead the efforts to harden our systems, ensuring our groundbreaking AI is built on an unshakeable base, working closely with the research team and the Applied ML teams to ensure the infrastructure is stable, reliable and can operate with more data and larger models as we grow.
What You Will Do: You will own the end‑to‑end strategy for platform reliability, with a specific focus on our accelerator (GPU/TPU) infrastructure and workload orchestration. You will move between high‑level architectural design and hands‑on systems engineering to eliminate friction in the researcher experience. Lead the reliability work for our global job scheduler. You will design and implement a robust “test harness” to safely validate infrastructure upgrades without impacting live research. Architect and optimize our next‑generation inference services. You will solve core scaling limits, ensuring high‑throughput performance and feature parity across our model serving stack. Overhaul our logging and monitoring systems to provide radical visibility. You will build proactive alerting and telemetry that identifies systemic failures before they impact research workflows. Improve our internal CI/CD stability, targeting a significant reduction in failure rates and significantly faster feedback loops for the engineering organization. Contribute to core technical decisions on tooling and architectural design while partnering with science, product, and operations teams to align infrastructure with biotech R&D cycles.
Skills and Qualifications:
- Essential: Proven experience in architecting and managing large‑scale AI/ML workloads in a production environment. Expertise in cloud compute design, specifically within Google Cloud Platform (GCP). Orchestration: Significant experience deploying and managing complex workloads within Kubernetes (GKE). Professional familiarity with NVIDIA GPU generations and the intricacies of high‑performance compute. Strong programming skills and a “reliability‑first” approach to software development.
- Nice to Have: A career history that spans both ML Software Engineering and Infrastructure SRE roles. Experience leading multi‑disciplinary projects and navigating complex stakeholder requirements in a fast‑paced environment. Familiarity with workload scheduling, ML efficiency research, and hardware benchmarking. Experience with Google TPU generations and specialized ML‑driven R&D cycles.
Culture and values: 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 at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less. 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 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.
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. 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.
Principal Software Engineer, ML Platform (Stability & Infrastructure) employer: Dormont Manufacturing Co
Iso Isomorphic Labs is an exceptional employer, fostering a culture of curiosity, creativity, and collaboration in the heart of biotech innovation. With a commitment to employee growth and a hybrid working model, we empower our team to make meaningful contributions towards curing diseases using cutting-edge AI technology. Join us to be part of a mission-driven environment where your expertise will directly impact the future of healthcare.
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Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Dormont Manufacturing Co.
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How to prepare for a job interview at Dormont Manufacturing Co
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
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Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
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While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.