Senior Software Engineer - Scalable Machine Learning

Metro Detroit, MIfull timeOn Site

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senior

$179k–$269k

H1B: yes

Latitude Senior Software Engineer - Scalable Machine Learning at Latitude designs and implements cloud services for data ingest, workflow orchestration, and distributed training. The role focuses on improving ML model training efficiency and managing large-scale multi-sensor training data.

Responsibilities

Scaling our machine learning models with data is vital to achieve optimal performance and to enable a safer and more sustainable future of transportation. In the Scalable ML team, we are looking at methods to improve the efficiency of model training, enabling ML developers to work efficiently with large volumes of data.
As a SWE for the Scalable ML team, you will:
Design, and implement state-of-the-art cloud services for data ingest, workflow orchestration, and distributed training at scale
Develop solutions to generate, manage, and process large amounts of multi-sensor training data for machine learning
Drive advanced MLOps practices, including model artifact management, experiment tracking, and automated model deployment and testing strategies
Collaborate closely with cross-functional teams, perception experts, and roboticists to integrate ML pipelines and ensure the delivery of high-quality, production-ready software
Mentor junior engineers and provide technical guidance to elevate the team's software development standards

Qualification

Experience designingMaster's or PhD in Computer Science

Required

Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
Strong track record of successfully delivering complex software projects from conception to production
Proven expertise in developing and optimizing machine learning data pipelines, data generation, and distributed model training
Experience designing, building, and operating large-scale distributed systems and cloud infrastructure
Strong proficiency in Python and/or C++ for developing high-performance, production-quality software

Preferred

Master's or PhD in Computer Science, Electrical Engineering, Robotics, or a closely related field
Hands-on experience with distributed machine learning frameworks and tools such as Ray, PyTorch, Dagster, LakeFS, or PyArrow
Experience with multi-sensor data fusion and processing techniques relevant to autonomous driving applications
Familiarity with safety-critical software development principles in automotive or robotics domains
Deep understanding of machine learning concepts, computer vision use cases, and the challenges of L2/L3 autonomy