Tech Lead Engineer, Physical AI Infrastructure

ByteDance

• $254K — $480K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or above in a technical field or equivalent experience.
  • 5 years of experience in software engineering, machine learning systems, or robotics.
  • 3+ years as a technical team lead.
  • Deep expertise in robotic learning, AI infrastructure, or robotics simulation processes.
  • Proven experience in taking complex systems from prototype to deployment.

Responsibilities

  • Track academic and industry advances, contributing technical insights and publications.
  • Own technical strategy and roadmap for Physical AI infrastructure areas.
  • Lead architecture and delivery across teams, ensuring accountability for technical outcomes.
  • Define interfaces for the Physical AI lifecycle and directly own major platform components.
  • Mentor engineers and develop technical leaders within the team.

Benefits

  • Day one access to medical, dental, and vision insurance.
  • 401(k) savings plan with company match.
  • Paid parental leave and short-term/long-term disability coverage.
  • 10 paid holidays and 10 paid sick days annually.
  • 17 days of Paid Personal Time, increasing with tenure.
Full Job Description
Responsibilitie

The Infra-Compute division builds large-scale, highly available cloud and AI infrastructure that powers our public cloud offerings and internal products. Our US team develops technologies across AI training, inference, and agent infrastructure. We are expanding this work into Physical AI: intelligent systems that perceive, reason, and act in the physical world. The team focuses on infrastructure for Physical AI, including data and simulation platforms, distributed training and inference, and deployment on heterogeneous hardware. We collaborate closely with customers, researchers, open-source communities, and hardware partners to turn emerging research into reliable, scalable systems. Responsibilities - Track advances in academia, industry, and open-source communities; contribute technical insights, software, and, where appropriate, publications. - Own the technical strategy and multi-quarter roadmap for major Physical AI infrastructure areas, translating ambiguous research, product, and customer requirements into clear architecture and execution plans. - Lead architecture and delivery across multiple engineers and partner teams, define system boundaries and interfaces, resolve cross-stack trade-offs, and remain accountable for end-to-end technical outcomes. - Define interfaces across the Physical AI lifecycle-including data pipelines, simulation, model training, evaluation, inference, and deployment-while directly owning one or more major platform components. - Mentor engineers, develop technical leaders, and raise the engineering bar across the team.

Qualification

Minimum Qualification(s) - Bachelor's degree or above in Computer Science, Computer Engineering, Robotics, Electrical Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience. - 5 years of software engineering, machine learning systems, robotics, or related industry experience. - 3+ years of experience as a tech lead. - Deep expertise in at least one of the following areas, with working knowledge across one or more of the others: robotic learning, including imitation learning, reinforcement learning, vision-language-action models, world models, or policy evaluation; AI training and inference infrastructure, including distributed training, inference engines, GPU kernels, or collective communication; robotics data and simulation systems, including multimodal dataset verification, synthetic data generation, simulation, data curation, or sim-to-real workflows. - Experience taking technically complex systems from prototype through validation and production deployment. - Strong communication skills, self-motivation, sound engineering judgment, and the ability to work effectively across research and engineering teams. Preferred Qualification(s) - Contributions to relevant open-source projects such as Isaac Lab, Isaac Sim, MuJoCo, Cosmos, vLLM-Omni, SGLang Omni, RLInf, etc. - Experience building large-scale AI or robotics platforms used by multiple teams or external customers, or experience with real-world robot systems and operational challenges. - Publications at leading machine learning, systems, or robotics conferences.

Job Information

【For Pay Transparency】Compensation Description (Annually)

The base salary range for this position in the selected city is $254400 - $480000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

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