招聘

AI Performance Optimization Engineer
New York, New York, United States; San Francisco, California, United States
·
On-site
·
Full-time
·
1mo ago
必备技能
PyTorch
Machine Learning
Who We Are
Lightning AI is the company behind Py Torch 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.
Our Values Move Fast: We act with speed and precision, breaking down big challenges into achievable steps.
Focus: We complete one goal at a time with care, collaborating as a team to deliver features with precision.
Balance: Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.
Craftsmanship: Innovation through excellence. Every detail matters, and we take pride in mastering our craft.
Minimal: Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.
What We're Looking For
We are seeking a highly skilled AI Optimization Engineer to work on optimizing training and inference workloads on compute accelerators and clusters, through the Lightning Thunder compiler and the broader Py Torch Lightning ecosystem. This role sits at the intersection of deep learning research, compiler development, and large-scale system optimization. You’ll be shaping technology that pushes the boundaries of model performance and efficiency, creating foundational software that will impact the entire machine learning ecosystem.
You will be joining the Engineering Team and report to our Tech Lead. This is a hybrid role based in either our New York City or San Francisco office with in-office requirements of 2 days per week. The salary range for this role is $120,000-$250,000.
What you’ll do
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Develop performance-oriented model optimizations at multiple levels:
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Graph-level (e.g., operator fusion, kernel scheduling, memory planning)
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Kernel-level (CUDA, Triton, custom operators for specialized hardware)
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System-level (distributed training across GPUs/TPUs, inference serving at scale)
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Advance the Thunder compiler by building optimization passes, graph transformations, and integration hooks to accelerate training and inference workloads.
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Work across the software stack to ensure optimizations are accessible to end users through clean APIs, automated tooling, and seamless integration with Py Torch Lightning.
Design and implement profiling and debugging tools to analyze model execution, identify bottlenecks, and guide optimization strategies. -
Collaborate with hardware vendors and ecosystem partners to ensure Thunder runs efficiently across diverse backends (NVIDIA, AMD, TPU, specialized accelerators).
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Contribute to open-source projects by developing new features, improving documentation, and supporting community adoption.
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Engage with researchers and engineers in the community, providing guidance on performance tuning and advocating for Thunder as the go-to optimization layer in ML workflows.
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Work cross-functionally with Lightning’s product and engineering teams to ensure compiler and optimization improvements align with the broader product vision.
What you’ll need
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Strong expertise with deep learning frameworks such as Py Torch
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Hands-on experience with model optimization techniques, including graph-level optimizations, quantization, pruning, mixed precision, or memory-efficient training.
Deep understanding of compiler internals (IR design, operator fusion, scheduling, optimization passes) or proven work in performance-critical software. -
Experience with CUDA, Triton, or other GPU programming models for developing custom kernels.
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Knowledge of distributed systems and parallelism strategies (data/model/pipeline parallelism, checkpointing, elastic scaling).
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Familiarity with software engineering practices: designing APIs, building robust tooling, testing, CI/CD for performance-sensitive systems.
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Proven track record contributing to open-source projects in ML, HPC, or compiler domains.
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Excellent collaboration and communication skills, with the ability to partner across research, engineering, and external contributors.
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Bachelor’s degree in Computer Science, Engineering, or a related field. Advanced degree (Master’s or PhD) in machine learning, compilers, or systems highly preferred.
Benefits and Perks
We offer competitive base salaries and equity with a 25% one year cliff and monthly vesting thereafter. For our international employees, we work with our EOR to pay you in your local currency and provide equitable benefits across the globe.
In the US, we offer:
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Medical, dental and vision
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Life and AD&D insurance
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Flexible paid time off including winter closure
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Paid family leave benefits
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$500 monthly meal reimbursement, including groceries & food delivery services
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$500 one time home office stipend
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$1,000 annual learning & development stipend
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100% Citibike membership (NYC only)
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$45/month gym membership
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Additional various medical and mental health services
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.
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关于Lightning AI

Lightning AI
Series ALightning AI develops PyTorch Lightning, an open-source deep learning framework that simplifies machine learning model training and deployment. The company provides cloud infrastructure and tools for AI researchers and developers.
51-200
员工数
New York
总部位置
$200M
企业估值
评价
3.9
10条评价
工作生活平衡
4.0
薪酬
3.2
企业文化
4.1
职业发展
2.8
管理层
2.9
72%
推荐给朋友
优点
Great work-life balance
Supportive and collaborative team
Good benefits and flexible hours
缺点
Management issues and poor communication
Limited career advancement opportunities
Workload and stress concerns
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