Who We Are
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 Way We Work
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.
What We're Looking For
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
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.
Benefits may vary by location, team, and role.
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.
