Role: On Device ML Engineer
Location: San Diego
Salary: Circa $175,000
Company Description
We are working with a global design and technology company specializing in connected consumer electronics and IoT products. With over 600 engineers worldwide, we combine advanced labs, cross-functional expertise, and a collaborative culture to bring some of the most demanding products to market. In the U.S., we have offices in San Diego, San Jose, and Seattle, providing engineers the chance to work on cutting-edge devices while enjoying a supportive, Nordic-inspired work culture that values work-life balance and knowledge-sharing.
Role Overview
We’re seeking a Software / ML Engineer to join our Wearable System Architect team. You’ll focus on power and performance optimization for on-device ML, working closely with cross-functional teams to define workload partitions, benchmark ML models, and analyze performance metrics. This is a hands-on technical role, ideal for engineers with embedded, RTOS, and consumer product experience who enjoy solving real-world ML deployment challenges.
Key Responsibilities
- Collect power and performance measurements from ML benchmarks (e.g., MLPerf-Tiny) across multiple hardware configurations.
- Compile and run ML models on different on-device ML accelerators, internal vs. external memory, and varied runtime environments.
- Analyze benchmark results to define workload partitions for ML accelerators and create PnP (Power & Performance) guidelines.
- Modify ML models (e.g., CNN layers, fully connected layers) to study the effect of model parameters on PnP metrics.
- Identify optimization opportunities in AI-driven use cases to improve device efficiency.
- Work closely with Wearable System Architects and cross-functional teams to implement and validate findings.
Experience Needed
- BS in Computer Science, Computer Engineering, or related field.
- 2+ years of consumer product experience (phones, wearables, smart devices).
- Hands-on experience with RTOS, Android, and embedded development environments.
- Familiarity with ML development environments and ability to port, compile, and run ML models on-device.
- Strong firmware knowledge for TinyML or MCU-based implementations.
- Ability to switch between technical contexts and collaborate across multiple teams.
- Strong problem-solving, critical thinking, and communication skills.
Compensation & Benefits
💰 Salary: $175,000
Comprehensive benefits package including:
- Paid time off, vacation, and holidays
- 401(k) with company match
- Basic Life / AD&D insurance
- Flexible Spending Accounts (Healthcare & Dependent Care)
- Health Savings Account (HSA)
- Paid parental and bereavement leave
- Employee assistance program
- Employee & customer referral programs
- Short-term and long-term disability insurance (varies by state)
