Lead Research Engineer

Job Application for Lead Research Engineer at Lightning AI

Lead Research Engineer London, England, United Kingdom; New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States

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.

What We're Looking For

We are seeking a highly skilled Lead Research Engineer to lead optimization efforts for training and inference workloads running on Lightning AI infrastructure. This role sits at the intersection of ML systems, AI infrastructure, performance engineering, and practical research. You’ll drive improvements across models, inference systems, and platform infrastructure to improve performance, scalability, and reliability for real-world AI workloads.

This is a highly cross-functional role that combines deep technical leadership with hands-on implementation. Successful candidates are comfortable operating broadly across the stack — from model behavior and inference systems to distributed infrastructure and developer tooling — while partnering closely with customers and internal engineering teams to solve complex AI systems challenges at scale.

This role is based in one of our hubs (NYC, SF, London, or Seattle — NYC and London are preferred), with a minimum of 2 in-office days per week and occasional team and company offsites.

What You'll Do

Lead optimization efforts for large-scale training and inference workloads across GPUs, accelerators, and distributed systems

Partner directly with customers to analyze workloads, identify bottlenecks, and drive improvements in performance, scalability, and reliability of deployed AI systems

Architect and improve inference pipelines, model serving systems, and performance-oriented tooling for production AI workloads

Lead the design and implementation of profiling, debugging, and observability tools to analyze model execution and guide optimization strategies

Drive performance improvements across the software stack through clean APIs, automation, and seamless integration with the Lightning ecosystem

Collaborate cross-functionally with infrastructure, product, and research teams to shape technical direction and improve the developer and user experience for AI workloads running on Lightning

Partner with hardware vendors and ecosystem partners to support efficient execution across diverse compute backends (NVIDIA, TPU, and emerging accelerators)

Contribute technical leadership to open-source projects through new features, tooling improvements, documentation, and community engagement

Stay current with advancements in large-scale inference, distributed training, and ML systems optimization, and help guide adoption of new technologies and approaches

What You’ll Need

Required Qualifications

Strong expertise with deep learning frameworks such as PyTorch

Significant experience working with large-scale training or inference workloads

Strong understanding of distributed systems and parallelism strategies (data/model/pipeline parallelism, checkpointing, elastic scaling, distributed inference)

Strong software engineering fundamentals, including designing APIs, building tooling, debugging complex systems, and shipping production-quality code

Experience leading or driving performance optimization efforts across ML systems, infrastructure, or distributed workloads

Hands-on experience with inference optimization techniques such as quantization, mixed precision, speculative decoding, memory-efficient training, or throughput/latency optimization

Experience with modern ML systems and inference tooling such as TensorRT, vLLM, SGLang, Dynamo, Triton, DeepSpeed, or related technologies

Excellent collaboration and communication skills, including the ability to partner directly with customers, cross-functional teams, and external contributors

Ability to operate effectively in ambiguous, fast-moving environments and drive technical direction across multiple layers of the stack

Master’s or PhD in Computer Science, AI, Machine Learning, Systems, Engineering, or a related field

Nice-to-Haves

Experience contributing to or leading open-source ML, infrastructure, or AI systems projects

Experience working closely with hardware vendors or accelerator ecosystems

Startup experience or experience operating in highly cross-functional environments

Experience mentoring engineers or leading technical initiatives across teams

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: $225,000 - $275,000 USD

Benefits and Perks

We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success. Benefits may vary by location, team, and role.

Benefits include:

Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)

Retirement and financial wellness support (U.S.); Pension contribution (U.K.)

Generous paid time off, plus holidays

Paid parental leave

Professional development support

Wellness and work-from-home stipends

Flexible work environment

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,…