Edge ML Software Engineer (Model Optimization-PICO) - San Jose

ByteDance; San Jose (CA); On-site; USD 212,800 - 450,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) with match

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Paid holidays

Paid sick days

Paid personal time

Job summary

ByteDance seeks an Edge ML Software Engineer for the Pico project in San Jose. The role focuses on converting and compiling ML models for edge NPUs, with emphasis on hardware-aware optimizations and quantization techniques.

You will profile power and performance across simulators and silicon, identifying bottlenecks in compute and memory workflows. The candidate should have strong Python/C++ skills and hands‑on experience with PyTorch and TensorFlow, plus a background in CNNs/Transformers.

Qualifications

• Master's degree or equivalent practical experience in a related field.
• 3+ years of industry experience in ML software engineering, model deployment, or ML systems for production environments.
• Strong understanding of deep learning architectures including CNNs and Transformers.
• Knowledge of ML accelerators' architectures, operator fusion, memory hierarchies, and data movements.
• Practical experience with PyTorch and TensorFlow.
• Proficiency in Python and C/C++.

Responsibilities

• Convert and compile ML models for edge NPUs, applying quantization mechanisms.
• Profile and analyze model performance and power consumption on simulators, emulators, and silicon.
• Identify bottlenecks related to compute, memory bandwidth, data movement, and scheduling.
• Apply hardware-aware optimization strategies, such as quantization, compression and operator fusion, to meet latency, memory and power targets.
• Collaborate with algorithm, compiler, firmware and hardware teams to debug functional and performance issues.

Skills

CNNs/Transformers

Python

C/C++

PyTorch

TensorFlow

Education

Master's degree in CS/EE/CE or related field

Tools

PyTorch

TensorFlow

Job description

Edge ML Software Engineer (Model Optimization-PICO) - San Jose

Location: San Jose

Team: Technology

Employment Type: Regular

Job Code: A143350B

Responsibilities

• Convert and compile ML models for execution on edge NPUs, and apply quantization mechanisms.
• Profile and analyze model performance and power consumption on simulators, emulators, and silicon platforms.
• Identify bottlenecks related to compute, memory bandwidth, data movement, and scheduling.
• Apply hardware‑aware optimization strategies, such as quantization, compression and operator fusion, to meet latency, memory and power targets.
• Work closely with algorithm, compiler, firmware and hardware teams to debug functional and performance issues.

Qualifications

Minimum Qualifications

• Master's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent practical experience.
• 3+ years of industry experience in machine learning software engineering, model deployment, or ML systems for production environments.
• Strong understanding of deep learning architectures, including CNNs and Transformers.
• Knowledge of ML accelerators' architectures, operator fusion, memory hierarchies, and data movements.
• Practical experience with popular ML frameworks, like PyTorch / TensorFlow.
• Proficiency in Python and C/C++.

Preferred Qualifications

• 5+ years of industry experience in machine learning software engineering, model deployment, or ML systems for production environments.
• Understanding of model inference constraints on edge devices, including latency, power, and accuracy trade-offs and optimization techniques.
• Understanding of quantization techniques, such as PTQ and QAT.

Job Information

The base salary range for this position in San Jose is $212,800 - $450,000 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

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.

EEO Statements

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;
3. Exercising sound judgment.

About Pico

Founded in April 2015, Pico is a VR company committed to developing immersive and interactive VR experiences for people around the world. Pico also provides tailor‑made solutions for our enterprise clients in the fields of education and healthcare.

Reasonable Accommodation

ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request