Sr. Systems Engineer
Job Description
A leader in the Mixed Reality space is seeking a Sr. Systems engineer to optimize the power and performance of it's systems. If you are well-versed in On Device Embedded engineering, Android, RTOS and Perfetto, apply today!Onsite in San Diego, CA (3-5 days in office per week)
This position requires employment on a W-2 basis only; we are not able to hire independent contractors or individuals working through a corporation (C2C). Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
*Description*
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.
*Provide clear PnP guidelines for ML model architectural exploration
*End-to-End power and performance optimization of AI driven use cases.
In this role, the candidate will be under the guidance of the Wearable System Architects and work closely with cross functional teams.
Roles and Responsibilities
* Collect power and performance measurement results and traces of ML benchmarks (e.g., MLPerf-Tiny).
* Execute ML benchmarks under different on-device configurations, for example:
o Execute ML benchmark on different on device ML accelerators.
o Execute ML benchmark on slow/external memory and fast/internal memory
* For this, the candidate needs to able to compile an existing ML model against different ML accelerators using corresponding ML compilers. The candidate also needs to be familiar with RTOS and Android development and run-time environments.
* Analyze above results to reveal PnP (Power and Performance) characterization of different ML accelerators.
o This will eventually lead to the workload partition definition, i.e., which type of ML workload will be more suitable on which ML accelerators.
* Modify ML benchmark models by varying different key ML model parameters. For example:
o Increase # of MACs significantly while keeping memory throughput relatively steady or vice-versa.
* Analyze above results in order to reveal the relationship between key ML model parameters (e.g., # of MACs) and PnP metrics
o This will eventually lead to PnP guideline that can help project PnP metrics based on values of key ML model parameters.
*Collect power and performance traces of AI driven use cases and identify areas of optimization.
*Additional Skills & Qualifications*
* 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.
Preferred Qualifications
* Familiar with Android based performance profiling tool: Perfetto.
* MS in Computer Science or Computer Engineering with courses on ML and computer architecture.
* 3+ consumer product (e.g. Phone, Watch, Glass or other) experience.
* Familiar with RTOS, Android and embedded development environment.
* Familiar with ML development environment. Able to construct ML model using either PyTorch or Tensor Flow.
* Familiar with ML accelerator and corresponding compilers: either ARM U55/U65/U85 and Vela compiler or QCOM's NSP and corresponding AI SDK.
o Able to compile and execute the ML models on ML accelerators.
o Able to collect instrument the ML execution and collect profiling results.
* Understand basics of power measurement.
* The ideal candidate will have 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. This will require the candidate having skills to port and compile ML models to run on device.
*Pay and Benefits*
The pay range for this position is $70.00 - $90.00
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
* Medical, dental & vision
* Critical Illness, Accident, and Hospital
* 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available
* Life Insurance (Voluntary Life & AD&D for the employee and dependents)
* Short and long-term disability
* Health Spending Account (HSA)
* Transportation benefits
* Employee Assistance Program
* Time Off/Leave (PTO, Vacation or Sick Leave)
*Workplace Type*
This is a fully onsite position in San Diego,CA.
*Application Deadline*
This position will be accepting applications until Feb 4, 2025.
About TEKsystems:
We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.
The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
*Please mention you saw this ad on NativeAmericansInHigherEducation.*
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