Senior Machine Learning Engineer

Description
Role: This Role is part of the Data Search and Mining group, the organization is responsible for providing high quality data for our Foundational Drive Model's training and evaluation at scale. We utilized Multi-Modality Model, VLM, MLLM to provide high precision search and mining solutions for AV training and evaluation. This role will play a critical piece on accelerating experiments on cutting edge search capability and SOTA models, then productionize them to company scale. Provide scalable and cost-efficient mining solutions that are able to handle PB-level data. Support key training and evaluation projects across the company.
The specific duties may include Multi-Modality MLLM model evaluation, fine-tuning, deployment, as well as bulk inference. Evaluate data quality and improve it. Provide cost estimation and analysis. Build and Utilize AI-Agent capability. Support data pipeline orchestration on distributed backend system.
What You'll Do:

• Evaluate and apply SOTA multiple modality machine learning models to search and mining needs

• Modern ML modeling skills, perform fine-tuning, evaluation

• Integration with other company level infrastructure such as Data infrastructure, compute platform, labeling, as well as simulation

• Strong software engineering (SWE) skills, focusing on distributed backend development, batch data processing

• Support autonomous vehicle (AV) technologies, understand the data challenges in AV or Robotic industry

• Enthusiastic to experiment and learn the latest AI development

Your Skills & Abilities:

• 4+ years of experience in the field of robotics or latency-sensitive backend services

• Proven experience in machine learning and classification. Familiar with ML frameworks such as Tensorflow or PyTorch

• Experience building highly performant ML and system pipelines

• Strong programming skills in modern C++ or Python

• Experience with profiling CPU and/or GPU software, process scheduling, and prioritization

• Passionate about self-driving car technology and its impact on the world

• Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions.

• Ability to design across multiple systems. Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain.

• Ability to wear several hats shifting between coding, design, technical strategy, and mentorship combined with excellent judgment on when to switch contexts to meet the greatest need.

• Experience working with Multiple Modality models

Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

• The salary range for this role is $134,000 to $205,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times a week, at minimum.
Relocation: This job may be eligible for relocation benefits.
#LI-MH2
This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.
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