Machine Learning Engineer 3

TrueCar, Inc.•Santa Monica, CA

4d•$184,558 - $195,000•Remote

About The Position

TrueCar, Inc. is seeking a Machine Learning Engineer 3 to design and deploy machine learning models into production, ensuring they meet performance, latency, memory, and throughput requirements. This role involves writing and implementing high-quality code, building and implementing machine learning models, and identifying issues in data distribution that could affect model performance. The engineer will troubleshoot complex problems with multilayered data sets, optimize existing machine learning libraries and frameworks, and collaborate with stakeholders to translate business issues into machine learning solutions. The goal is to create models that drive real value for consumers and deal partners, while staying current with machine learning technology developments and sharing best practices. Full-time telecommuting is permitted from anywhere in the U.S.

Requirements

Master’s degree, or foreign equivalent, in Computer Science, Data Science, or a closely related field plus 2 years of experience in the job offered or a related occupation.
Employer will accept a Bachelor’s degree, or foreign equivalent, in Computer Science, Data Science, or a closely related field plus 5 years of progressively responsible experience in the job offered or a related occupation.
Python (2 years)
Machine learning frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn (2 years)
Deep learning and training neural networks (2 years)
AWS SageMaker (2 years)
Chain-of-Thought Prompt Engineering (2 years)
Experience with Langchain or similar Agentic Framework Library (2 years)
Experience with AI Detectors (2 years)
Language translation and content production using LLMs (large language models) (2 years)

Responsibilities

Design and deploy machine learning models into production, ensuring they meet performance, latency, memory, and throughput requirements.
Write and implement high-quality code.
Build and implement machine learning models.
Identify issues and differences in data distribution that could potentially affect model performance.
Troubleshoot and solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.
Collaborate with stakeholders to fuse ideas from business issues to machine learning solutions.
Create models that drive real value for consumers and deal partners.
Stay up to date with developments in machine learning technology and proactively share best practices.