Senior Machine Learning Engineer- Trajectory Generation

United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, Robotics, AI & Machine LearningIndustries

Requirements

Candidates must possess a Master's or Ph.D. in Robotics, Computer Engineering, or a related field, with proficiency in both C++ and Python. A minimum of 4 years of experience in designing, training, and deploying ML models is required, along with a strong understanding of trajectory optimization, reinforcement learning, and imitation learning algorithms. Publications in Machine Learning or Robotics-related venues are also required. Bonus points include experience with autonomous driving applications, CUDA, inference optimization, and publications in reinforcement learning, inverse reinforcement learning, optimal control, or robotics.

Responsibilities

The Senior Machine Learning Engineer will research, design, implement, optimize, and deploy deep learning models for data-driven control algorithms in trajectory and path generation. Responsibilities include designing reward functions to improve vehicle behavior, developing tools and metrics for error analysis and performance measurement, optimizing model and system performance for real-time inference, and participating in code and design reviews.

Skills

C++

Python

Trajectory Optimization

Reinforcement Learning

Imitation Learning

Machine Learning Models

Deep Learning

Control Algorithms

Autonomous Driving

CUDA

Inference Optimization

Robotics

Problem-Solving

Motional

Develops fully driverless robotaxis for urban transport

About Motional

Motional develops fully driverless vehicles, specifically robotaxis, aimed at transforming urban transportation. Their all-electric robotaxis are designed to navigate complex city environments safely and efficiently. Motional partners with ride-hailing and delivery services, providing them with advanced autonomous vehicle technology to enhance their operations and reduce costs. A unique aspect of Motional's service is its Command Center, which allows for real-time tracking of each robotaxi, enabling human agents to monitor performance and ensure passenger safety. Unlike many competitors, Motional focuses on integrating its vehicles into existing mobility networks, making driverless technology accessible and reliable. The company's goal is to make autonomous vehicles a safe and integral part of urban transportation.

Boston, MassachusettsHeadquarters

2020Year Founded

$5,000MTotal Funding

GROWTH_EQUITY_NON_VCCompany Stage

Robotics & Automation, Automotive & TransportationIndustries

1,001-5,000Employees

Benefits

401K: 401K with up to 7.5% match

time Off: Unlimited sick and vacation days

Transportation: Commuter and fitness benefits

Healthcare: 3 plan options to support diverse needs

IVF: Fertility assistance

Risks

Motional laid off 550 employees, indicating financial and operational challenges.

Aptiv reduced its stake in Motional, impacting operational capabilities.

Delays in autonomous vehicle deployment to 2026 could hinder market entry plans.

Differentiation

Motional offers a state-of-the-art Command Center for real-time robotaxi tracking.

The company focuses on all-electric, driverless robotaxis for urban environments.

Motional partners with ride-hailing services to integrate autonomous vehicles into their operations.

Upsides

Motional raised $475 million from Hyundai, indicating strong financial backing.

Partnerships with Uber and Shake Shack expand Motional's market reach in delivery services.

Increased investment in robotics highlights potential funding opportunities for Motional.

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