Software Engineer, AI Performance Modeling & Co Design
Tesla
Software Engineer, AI Performance Modeling & Co Design
Job Description
The AI co-design team is dedicated to developing and optimizing AI systems that can scale efficiently to thousands of compute nodes, enabling large-scale training, reinforcement learning at scale, and real-time inference for Autopilot and Optimus. Our goal is to push the boundaries of performance, power, and latency on our custom-designed AI-ASIC cluster, while delivering exceptional scalability and performance. This unique position sits at the intersection of AI research, performance modeling, and system design. You will work closely with AI engineers to optimize model architectures, leveraging network topologies to efficiently parallelize and shard models on our cluster. Additionally, you will collaborate with our hardware co-design team to model and optimize future generation performance, ensuring seamless integration of AI models and algorithms with next-generation hardware.
Locations
- Palo Alto, California, United States
Salary
132,000 - 390,000 USD / yearly
Estimated Salary Rangehigh confidence
180,000 - 320,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in Python and C++intermediate
- Experience with AI networks, such as CNNs, transformers, and diffusion model architectures, and their performance characteristicsintermediate
- Experience with parallel computing frameworks and libraries, such as MPI, NCCL, or Gloointermediate
- Understanding of GPU and TPU accelerators architecture, memory hierarchy, and ability to model performance and identify performance bottlenecksintermediate
- Strong understanding of computer networks, including network protocols, topology, and performance modelingintermediate
- Experience with SW/HW co-design and optimizationintermediate
- Strong analytical and problem-solving skills, with the ability to analyze complex systems and optimize their performanceintermediate
Required Qualifications
- Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, proof of exceptional skills in related fields with practical software engineering experience, or equivalent experience (experience)
- Experience in performance modeling, parallel computing, and networking, with a focus on AI systems (experience)
- Proficiency in Python and C++ (experience)
- Experience with AI networks, such as CNNs, transformers, and diffusion model architectures, and their performance characteristics (experience)
- Experience with parallel computing frameworks and libraries, such as MPI, NCCL, or Gloo (experience)
- Understanding of GPU and TPU accelerators architecture, memory hierarchy, and ability to model performance and identify performance bottlenecks (experience)
- Strong understanding of computer networks, including network protocols, topology, and performance modeling (experience)
- Experience with SW/HW co-design and optimization (experience)
- Strong analytical and problem-solving skills, with the ability to analyze complex systems and optimize their performance (experience)
Responsibilities
- Develop and apply performance modeling techniques to analyze and optimize AI system performance, including dataflow, mapping, and sharding of AI models
- Design and implement collective and multi-device parallel computing algorithms and architectures to accelerate AI workloads
- Develop and maintain network models and simulations to analyze and optimize AI system performance in distributed environments
- Collaborate with cross-functional teams to integrate performance modeling and optimization techniques into AI system design and development workflows
- Develop and maintain software tools and frameworks to support performance modeling, parallel computing, and networking development
- Work closely with the hardware co-design team to model and optimize future generation AI-ASIC architectures, ensuring seamless integration of AI models and algorithms with next-generation hardware
- Co-design and optimize AI systems for future generations, considering emerging trends and technologies, such as 3D stacked processors, photonic interconnects, and novel memory architectures
- Develop and apply co-design methodologies to optimize AI system performance, power, and area, while ensuring scalability, reliability, and manufacturability
Benefits
- general: Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction
- general: Family-building, fertility, adoption and surrogacy benefits
- general: Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
- general: Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA
- general: Healthcare and Dependent Care Flexible Spending Accounts (FSA)
- general: 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
- general: Company paid Basic Life, AD&D, short-term and long-term disability insurance
- general: Employee Assistance Program
- general: Sick and Vacation time (Flex time for salary positions), and Paid Holidays
- general: Back-up childcare and parenting support resources
- general: Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
- general: Weight Loss and Tobacco Cessation Programs
- general: Tesla Babies program
- general: Commuter benefits
- general: Employee discounts and perks program
Tags & Categories
Software Engineer, AI Performance Modeling & Co Design
Tesla
Software Engineer, AI Performance Modeling & Co Design
Job Description
The AI co-design team is dedicated to developing and optimizing AI systems that can scale efficiently to thousands of compute nodes, enabling large-scale training, reinforcement learning at scale, and real-time inference for Autopilot and Optimus. Our goal is to push the boundaries of performance, power, and latency on our custom-designed AI-ASIC cluster, while delivering exceptional scalability and performance. This unique position sits at the intersection of AI research, performance modeling, and system design. You will work closely with AI engineers to optimize model architectures, leveraging network topologies to efficiently parallelize and shard models on our cluster. Additionally, you will collaborate with our hardware co-design team to model and optimize future generation performance, ensuring seamless integration of AI models and algorithms with next-generation hardware.
Locations
- Palo Alto, California, United States
Salary
132,000 - 390,000 USD / yearly
Estimated Salary Rangehigh confidence
180,000 - 320,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Proficiency in Python and C++intermediate
- Experience with AI networks, such as CNNs, transformers, and diffusion model architectures, and their performance characteristicsintermediate
- Experience with parallel computing frameworks and libraries, such as MPI, NCCL, or Gloointermediate
- Understanding of GPU and TPU accelerators architecture, memory hierarchy, and ability to model performance and identify performance bottlenecksintermediate
- Strong understanding of computer networks, including network protocols, topology, and performance modelingintermediate
- Experience with SW/HW co-design and optimizationintermediate
- Strong analytical and problem-solving skills, with the ability to analyze complex systems and optimize their performanceintermediate
Required Qualifications
- Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, proof of exceptional skills in related fields with practical software engineering experience, or equivalent experience (experience)
- Experience in performance modeling, parallel computing, and networking, with a focus on AI systems (experience)
- Proficiency in Python and C++ (experience)
- Experience with AI networks, such as CNNs, transformers, and diffusion model architectures, and their performance characteristics (experience)
- Experience with parallel computing frameworks and libraries, such as MPI, NCCL, or Gloo (experience)
- Understanding of GPU and TPU accelerators architecture, memory hierarchy, and ability to model performance and identify performance bottlenecks (experience)
- Strong understanding of computer networks, including network protocols, topology, and performance modeling (experience)
- Experience with SW/HW co-design and optimization (experience)
- Strong analytical and problem-solving skills, with the ability to analyze complex systems and optimize their performance (experience)
Responsibilities
- Develop and apply performance modeling techniques to analyze and optimize AI system performance, including dataflow, mapping, and sharding of AI models
- Design and implement collective and multi-device parallel computing algorithms and architectures to accelerate AI workloads
- Develop and maintain network models and simulations to analyze and optimize AI system performance in distributed environments
- Collaborate with cross-functional teams to integrate performance modeling and optimization techniques into AI system design and development workflows
- Develop and maintain software tools and frameworks to support performance modeling, parallel computing, and networking development
- Work closely with the hardware co-design team to model and optimize future generation AI-ASIC architectures, ensuring seamless integration of AI models and algorithms with next-generation hardware
- Co-design and optimize AI systems for future generations, considering emerging trends and technologies, such as 3D stacked processors, photonic interconnects, and novel memory architectures
- Develop and apply co-design methodologies to optimize AI system performance, power, and area, while ensuring scalability, reliability, and manufacturability
Benefits
- general: Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction
- general: Family-building, fertility, adoption and surrogacy benefits
- general: Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
- general: Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA
- general: Healthcare and Dependent Care Flexible Spending Accounts (FSA)
- general: 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
- general: Company paid Basic Life, AD&D, short-term and long-term disability insurance
- general: Employee Assistance Program
- general: Sick and Vacation time (Flex time for salary positions), and Paid Holidays
- general: Back-up childcare and parenting support resources
- general: Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
- general: Weight Loss and Tobacco Cessation Programs
- general: Tesla Babies program
- general: Commuter benefits
- general: Employee discounts and perks program
Tags & Categories