About this opportunity
Voltage Park lists this Research Engineer opportunity in new york city, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Lightning AI is the creator of PyTorch Lightning. We develop an end‑to‑end platform that helps bring AI from research to production more efficiently.
What We're Looking For
Research Engineer to optimize training and inference workloads on compute accelerators and clusters via the Lightning Thunder compiler and the PyTorch Lightning ecosystem. Hybrid role based in New York City, San Francisco, or London (two days in‑office per week). Salary range: $180,000–$250,000.
Responsibilities
Develop performance‑oriented model optimizations at multiple levels:Graph‑level (operator fusion, kernel scheduling, memory planning)
Kernel‑level (CUDA, Triton, custom operators for specialized hardware)
System‑level (distributed training across GPUs/TPUs, inference serving at scale)
Advance the Thunder compiler by building optimization passes, graph transformations, and integration hooks to accelerate workloads.
Work across the software stack to expose optimizations via clean APIs, automated tooling, and seamless integration with PyTorch Lightning.
Design and implement profiling and debugging tools to analyze execution, detect bottlenecks, and guide optimization strategies.
Collaborate with hardware vendors and ecosystem partners to ensure efficient back‑end support (NVIDIA, AMD, TPU, specialized accelerators).
Contribute to open‑source projects by adding new features, improving documentation, and fostering community adoption.
Engage with researchers and engineers, providing performance‑tuning guidance and advocating for Thunder as the go‑to optimization layer.
Work cross‑functionally with product and engineering teams to align compiler improvements with product vision.
Requirements
Strong expertise with deep learning frameworks such as PyTorch.
Hands‑on experience with model optimization techniques: graph‑level optimizations, quantization, pruning, mixed precision, memory‑efficient training.
Knowledge of distributed systems and parallelism strategies (data/model/pipeline parallelism, checkpointing, elastic scaling).
Familiarity with software engineering practices: API design, robust tooling, testing, CI/CD for performance‑sensitive systems.
Excellent collaboration and communication skills for cross‑functional partnerships.
Bachelor’s degree in Computer Science, Engineering, or related field.
Nice‑to‑Haves
Experience with CUDA, Triton, or other GPU programming models for custom kernels.
Deep understanding of deep learning compiler internals (IR design, operator fusion, scheduling, optimization passes) or a proven track record in performance‑critical software.
Proven contributions to open‑source projects in ML, HPC, or compiler domains.
Advanced degree (Master’s or PhD) in machine learning, compilers, or systems highly preferred.
Benefits
Competitive base salary and equity with a 25% one‑year cliff and monthly vesting thereafter.
Equitable benefits administered by an Employee‑Ownership‑Registry for international employees.
Benefits (US)
Medical, dental and vision coverage.
Life and AD&D insurance.
Flexible paid time off, including winter closure.
Paid family leave benefits.
$500 monthly meal reimbursement (groceries & food delivery services).
$500 one‑time home‑office stipend.
$1,000 annual learning & development stipend.
100% Citibike membership (NYC only).
$45/month gym membership.
Additional medical and mental‑health services.
At Lightning AI, we are committed to fostering an inclusive and diverse workplace. 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.
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Worksite address
new york city, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.