Principal Machine Learning Engineer - Perception at Motional

Singapore, Singapore

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Autonomous Driving, RoboticsIndustries

Requirements

Masters or Ph.D. in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience
Strong leadership skills at executing large, complex technical initiatives
In-depth understanding of common Machine Learning and Deep Learning algorithms
Experience with designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, multi-object tracking, and/or end-to-end perception
Experience with deep learning frameworks such as TensorFlow or PyTorch
Fluency in Python, including standard scientific computing libraries and Python bindings development experience
Proven track record of developing and deploying perception systems for autonomous vehicles or robotics
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
Excellent communication and interpersonal skills
Experience mentoring and leading others

Responsibilities

Lead the development and implementation of advanced perception algorithms for object detection, tracking, classification, and segmentation using camera, lidar, and radar data
Connect and drive business impact through technology solutions
Design and implement sensor fusion algorithms to combine data from multiple sensors to create a robust and accurate perception system
Optimize perception algorithms for real-time performance on embedded hardware
Collaborate with other engineers and teams to integrate perception systems into larger autonomous systems
Stay abreast of the latest research and advancements in machine learning and computer vision and apply them to real-world problems
Productionize and deploy solutions onto autonomous vehicle fleets
Derive good insight from large data sets from a variety of sources
Mentor and guide junior engineers on the team

Skills

Key technologies and capabilities for this role

Machine LearningDeep LearningNeural NetworksObject DetectionObject TrackingSemantic SegmentationInstance SegmentationSensor FusionLidarRadarComputer Vision

Questions & Answers

Common questions about this position

What education is required for the Principal Machine Learning Engineer role?

A Masters or Ph.D. in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, Physics or a related field, or equivalent industry experience is required.

What key technical skills are needed for this position?

Candidates need in-depth understanding of Machine Learning and Deep Learning algorithms, experience with neural networks for perception tasks like object detection and tracking, proficiency with TensorFlow or PyTorch, and fluency in Python including scientific computing libraries.

What leadership experience is expected?

Strong leadership skills at executing large, complex technical initiatives, experience mentoring and leading others, and a proven track record of developing and deploying perception systems are required.

What is the team environment like at Motional?

The Perception team consists of world-class ML engineers and research scientists working on tech for perceiving dynamic scenarios in robo-taxis, with a mission to make self-driving vehicles a reality and create positive social impact.

What makes a strong candidate for this role?

A strong candidate has a relevant advanced degree or equivalent experience, proven expertise in perception ML for autonomous vehicles, leadership in complex projects, and bonus points for embedded systems experience, publications in top conferences, or launching ML products.

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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