Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building learned models to develop and evaluate the Motion Planner in large scale simulations with an accent on using complex scenarios. Focus on augmenting simulation data and creating unseen realistic and plausible scenarios for training and evaluating the Motion Planner and other sub-systems.

Location: Mountain View, California

Salary: $139,000-$223,000 per year

Company

hirify.global’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.

What you will do

• Build learned models used to develop and evaluate the Motion Planner in large scale simulations on complex scenarios.
• Build novel generative models to augment simulation data and create unseen realistic and plausible scenarios for training and evaluating the Motion Planner and other sub-systems.
• Support the various parts of the ML model development workflow, including dataset management, label quality, feature processing pipelines, model training and evaluation infrastructure.
• Work closely with Behavior Planning and Safety Engineering teams to understand their requirements and inform our technical approach.
• Develop tools to visualize, introspect and extract insights from running our models.
• Support your team with code reviews and ideas as part of a collaborative environment.

Requirements

• Motivated and can work independently in a fast paced environment, navigating problem ambiguity.
• Strong knowledge of ML fundamentals.
• ML model building experience (data preparation, training, model design, evaluation)
• Robotics-related domain knowledge.
• Strong knowledge of PyTorch, Python, numpy and common data science libraries.
• 2+ years of industry experience in a related field.

Nice to have

• Experience with Motion Planner development.
• Experience deploying ML models in production environments.
• Project work, or publications in top-tier conferences or workshops.

Culture & Benefits

• Operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.