Device ML Power and Performance Optimization Engineer

Sigma Connectivity is a design house. We are a team of 700 talented engineers and our main office is located in Lund, Southern Sweden. Primarily we run in-house projects focusing on connected products within consumer electronics and IoT devices and we have the capability in terms of people, expertise and labs to realize the most demanding products on the market. In US we have offices in San Jose,San Diego and Seattle.

The San Diego office is located close to Palomar Airport in Carlsbad ,our office in San Jose is located just by the San Jose airport and our Seattle office is in the heart of Bellevue .As a fast-growing company we are constantly looking for open-minded, talented people who want to take part in our journey. The Sigma Connectivity company culture is about sharing experiences and knowledge and with a Nordic work culture we strive for work-life balance and taking care of people.

Within Sigma Connectivity you will never work alone.

We are seeking a highly skilled software/ML engineer to join the Wearable System Architect team and work on power and performance optimization of on device ML.

The area of focus and main problems to address are:

• Provide ML workload partition definition based on PnP characterization of ML accelerators.
• End-to-End power and performance optimization of AI driven use cases.
• Collect power and performance measurement results and traces of ML benchmarks (e.g.,
  MLPerf-Tiny
  ).
• Compile an existing ML model against different ML accelerators.
• Be familiar with RTOS and Android development and run-time environments.
• Analyze results to reveal PnP (Power and Performance)
  characterization of different ML accelerators.
• Modify an existing ML model by changing model parameters.
• Analyze results in order to reveal the relationship between key ML model parameters
• Collect power and performance traces of AI driven use cases and identify areas of optimization.
• BS in Computer Science or Computer Engineering
• 2+ consumer product (e.g. Phone, Watch, Glass or other) experience.
• Familiar with RTOS, Android and embedded development environment.
• Familiar with ML development environment.
• Strong firmware skills and will implement tiny ML on hardware/MCUs.
• Training the ML models including model architectural exploration is outside the scope of this job. But the candidate will need to modify ML models for the purpose of revealing the relationship between PnP metrics and ML model parameters.
• Skills to port and compile ML models to run on device.

• Team player
• Proactiveness in collaborating and execution.
• Flexibility to switch technical context
• Willingness to learn new methods / tools / processes
• Ability to prioritize and multitask
• Strong problem solving and critical thinking skills
• Strong passion for creativity and solving cutting edge industry problems
• Strong communication and interpersonal skills.

The annual salary range for this role is $80,000 – $250,000 per year.

The Annual Salary depends upon various job-related factors such as professional background, training, work experience, location, business needs, and market demand. This range is subject to change and may be modified in the future.

Sigma Connectivity Inc also offers a comprehensive benefits package that includes the following:

• Paid Time off/Vacation and Paid Holidays
• 401(k) matching
• Basic Life / AD&D insurance
• Flexible Spending Account (FSA):
  Healthcare and Dependent Care
• Health Savings Account (HSA)
• Employee Assistance Program
• Employee and Customer Referral Program.
• For position based in California and all other states (excluding Washington), we offer both short-term and long-term disability insurance. For positions based in Washington state, we offer long-term disability insurance only.

On Device ML Power and Performance Optimization Engineer

Sigma Connectivity Inc.

Testing and Verification, Software development embedded systems