Machine Learning Engineer – ML Agents, Planning

Jobtailor; Foster City (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

Jobtailor in Foster City, CA, is seeking a senior ML scientist to develop deep learning models for autonomous driving, using imitation and reinforcement learning to craft driving plans. You will estimate plan quality by safety, progress, comfort, and realism, and contribute to scalable ML infrastructure for discovering new solutions.

The role emphasizes production pipelines, transformer-based models, and collaboration across Perception, Planning, Simulation, and Validation teams.

Qualifications

• PhD in computer science or related field, or master's plus 5+ years of relevant experience.
• Experience in planning and/or prediction using reinforcement learning techniques.
• Experience with training and deploying transformer-based model architectures.
• Experience with production machine learning pipelines: dataset creation, training frameworks, metrics pipelines.
• Fluency in Python with a basic understanding of C++.

Responsibilities

• Develop deep learning models using imitation learning and reinforcement learning to generate driving plans.
• Estimate quality of driving plans across safety, progress, comfort, and realism.
• Contribute to large-scale ML infrastructure to discover solutions and push the boundaries of the field.
• Develop metrics and tools to analyze errors and understand improvements of our systems.
• Collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the Autonomous Driving problem.

Skills

Imitation Learning

Reinforcement Learning

Planning

Prediction

Metrics Development

Error Analysis

Dataset Creation

Training Frameworks

Python

C++

Education

PhD in Computer Science or related field

Master's + 5+ years of relevant experience

Tools

Transformer-based model architectures

Machine Learning Infrastructure

Python

C++

Job description

• You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like agents.
• You will work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.
• You will contribute to our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
• You will develop metrics and tools to analyze errors and understand improvements of our systems
• You will collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem.

Requirements

• PhD degree in computer science or related field or master's degree and 5+ years of professional experience in a relevant field.
• Experience in Planning and / or Prediction using Reinforcement Learning techniques
• Experience with training and deploying transformer-based model architectures
• Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
• Fluency in Python with a basic understanding of C++

Core Competencies

Expertise in developing deep learning models for autonomous driving, with a focus on imitation learning and reinforcement learning. Proficient in creating and analyzing machine learning pipelines, metrics, and tools to enhance system performance and safety.

Highest-signal resume keywords

• PhD In Computer Science
• Reinforcement Learning Techniques
• Transformer-Based Model Architectures
• Production Machine Learning Pipelines
• Fluency In Python

ATS Optimization Keywords

Hard Skills

• Deep Learning Models
• Imitation Learning
• Reinforcement Learning
• Planning
• Prediction
• Metrics Development
• Error Analysis
• Dataset Creation
• Training Frameworks
• Model Deployment

Industry Keywords

• Autonomous Driving
• Safety
• Comfort
• Realism
• Collaboration

Tools & Technologies

• Machine Learning Infrastructure
• Python
• C++