Research Engineer, AI/ML Systems

Research Engineer, AI/ML Systems

Full-Time 157500 - 192500 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Develop and improve AI systems while collaborating on innovative projects.
  • Company: Join Lightning AI, the creators of PyTorch Lightning, in a dynamic tech environment.
  • Benefits: Enjoy competitive salary, equity options, unlimited PTO, and wellness perks.
  • Other info: Flexible hybrid work model and opportunities for professional growth.
  • Why this job: Make a real impact in AI development and work with cutting-edge technologies.
  • Qualifications: Experience with deep learning models and strong software engineering skills required.

The predicted salary is between 157500 - 192500 £ per year.

Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems - designed to take ideas from research to production with less friction.

Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.

We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.

The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice:

  • Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.
  • Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.
  • Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.
  • Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work.
  • Raise the Bar: We’re always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.
  • Think Long-Term: We design for what’s next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact.

We’re looking for a curious, adaptable Research Engineer who enjoys solving difficult technical problems and building across the AI stack to join our Research Engineering function here at Lightning. This role is intentionally broad, with a primary focus on post-training models and the systems that support it. You’ll work across ML engineering, software engineering, and AI systems to improve how we develop, train, evaluate, and deploy models. As team priorities evolve, you’ll have opportunities to contribute across developer tooling, infrastructure, and platform capabilities that help researchers and customers develop, train, and deploy AI more effectively.

We’re looking for someone who enjoys learning new technologies, working across multiple technical domains, and tackling whatever problems have the greatest impact. Strong software engineering fundamentals, curiosity, and a willingness to continuously learn are more important than already being an expert in every area of AI systems. If you’ve spent meaningful time building AI projects, experimenting with PyTorch, contributing to open source, reproducing research, or exploring new ideas because you’re genuinely interested, we’d love to hear about it.

This role is hybrid with a minimum of 2 in-office days per week in San Francisco, Seattle, NYC, or London, with fully remote work considered for candidates outside of our office hub locations. All employees participate in occasional team and company offsites.

What You’ll Do

  • Develop and post-train models, while building and improving the systems and workflows needed to run, evaluate, debug, and scale training workloads.
  • Build software, tooling, and platform capabilities that improve how researchers, developers, and customers develop, train, and deploy AI systems.
  • Contribute to Lightning’s open-source projects by building new features, improving existing functionality, and collaborating with the broader developer community.
  • Work across deep learning systems, developer tooling, backend services, and platform infrastructure to solve a wide variety of engineering challenges.
  • Collaborate directly with customers to understand real-world AI workloads, investigate technical challenges, and translate those learnings into reusable product and platform improvements.
  • Prototype new ideas, evaluate approaches, and turn successful experiments into production-quality software.
  • Partner closely with research, product, and infrastructure engineering teams to improve developer experience, AI workflows, and platform capabilities.
  • Debug complex technical problems spanning machine learning, distributed systems, backend software, and developer tooling.
  • Learn new technologies quickly and contribute wherever your skills can have the greatest impact as team priorities evolve.

What You’ll Need

  • Required Qualifications: Experience building, training, evaluating, or experimenting with deep learning models. Hands-on experience with deep learning frameworks such as PyTorch. Strong software engineering fundamentals building software and debugging and problem-solving skills, with the ability to investigate unfamiliar technical challenges. Curiosity, initiative, and a demonstrated ability to quickly learn new technologies and technical domains. Excellent communication and collaboration skills, including the ability to work effectively across research, product, infrastructure, and customer-facing engagements. Comfortable working in fast-moving, ambiguous environments where priorities evolve over time. Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • Ideal Experience: Experience with model training at scale, including distributed training, performance optimization, training stability, and/or large-scale experimentation. Experience with transformer-based language models or modern generative AI systems. Experience with distributed systems, cloud infrastructure, or large-scale machine learning workloads. Familiarity with technologies such as CUDA, Hugging Face, DeepSpeed, FSDP, Triton, vLLM, SGLang, NVIDIA Molt, or related AI infrastructure tooling. Experience contributing to open-source software or conducting research through academia, industry, or meaningful independent projects. Startup experience or experience working on highly cross-functional engineering teams. Master's degree or higher in Computer Science, Machine Learning, AI, or a related field.

Compensation

We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $165,000 - $310,000 USD.

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success:

  • Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents.
  • Meaningful Equity: RSUs that give employees a stake in the company's long-term success.
  • Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.).
  • Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance.
  • Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge.
  • Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments.
  • Professional Development: Annual learning and development allowance to support your professional growth.
  • Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being.
  • Sabbatical Program: Four weeks of paid sabbatical leave after four years of service.
  • Flexible Work: Flexible schedules and a hybrid work model for our office-based teams.
  • In-Office Meals: Complimentary meals at our office hubs.

At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.

Research Engineer, AI/ML Systems employer: Lightning-Ai

Lightning AI is an exceptional employer that champions innovation and collaboration, making it an ideal place for a Senior Infrastructure Software Engineer to thrive. With a strong focus on professional development, competitive compensation, and a flexible work environment, employees are empowered to take ownership of their projects while enjoying comprehensive benefits that support their well-being. The company's commitment to diversity and inclusion fosters a vibrant work culture where every team member can contribute meaningfully to cutting-edge AI solutions.

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Contact Details:

Lightning-Ai Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Engineer, AI/ML Systems

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Lightning-Ai or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Lightning-Ai.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Lightning-Ai.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Lightning-Ai that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Research Engineer, AI/ML Systems

Deep Learning
PyTorch
Software Engineering Fundamentals
Problem-Solving Skills
Curiosity
Communication Skills
Collaboration Skills

Some tips for your application 🫡

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 Lightning-Ai.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Lightning-Ai and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Lightning-Ai

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.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Lightning-Ai uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

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.

Prepare for Behavioural Questions

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.