Senior Software Engineer, Unified Modeling (CVML)

Palo Alto, California, United States

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Automotive, Artificial Intelligence, AI & Machine Learning, Software DevelopmentIndustries

Requirements

Candidates must possess a Bachelor's or Master's Degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics, or a related field. Expertise in machine learning, with a proven track record of developing and deploying deep learning solutions using PyTorch, Tensorflow, or similar frameworks, is essential. Experience in developing perception systems using sensors like Camera, Radar, and LiDAR, along with strong computer vision, perception, and point cloud processing skills, is required. Proven experience in shipping computer vision software products to industry or consumers and at least 5 years of development experience in Python/C++ environments are also necessary. A Ph.D. with a machine learning focus or equivalent experience, and experience developing and deploying temporal computer vision models are considered advantageous.

Responsibilities

The Senior Software Engineer will develop spatio-temporal machine learning models for detection, multi-sensor fusion, and segmentation. Responsibilities include reading literature, analyzing raw data, designing state-of-the-art solutions, and transitioning these solutions from the lab to production-level implementation on test tracks and public roads. The engineer will collaborate with perception experts and roboticists on algorithm design, prototyping, testing, deployment, and productization, while also building and maintaining industry-leading software practices and principles. Developing clean and efficient software for perception modules that interface with other key modules and showing initiative in a fast-paced, innovative environment are also key duties.

Skills

Machine Learning

Computer Vision

Deep Learning

3D Object Detection

Lane Line Detection

State Estimation

Scene Segmentation

Robotics

Cloud Platforms

Sensors

Compute Systems

Python

C++

Latitude AI

Develops automated driving technologies for vehicles

About Latitude AI

Latitude AI develops automated driving technologies aimed at enhancing the driving experience. Their primary product is a hands-free, eyes-off driver assist system designed for next-generation Ford vehicles. This system allows drivers to engage in other activities while the vehicle manages driving tasks, thereby making driving safer and less stressful. Latitude AI stands out from competitors by combining the agility of a startup with the manufacturing capabilities of Ford, enabling rapid development and integration of advanced technologies into vehicles. The company's goal is to redefine how people interact with their cars, improving safety and providing drivers with more free time during their journeys.

Pittsburgh, PennsylvaniaHeadquarters

2022Year Founded

VENTURE_UNKNOWNCompany Stage

Robotics & Automation, Automotive & TransportationIndustries

201-500Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Health Savings Account/Flexible Spending Account

401(k) Retirement Plan

401(k) Company Match

Paid Parental Leave

Paid Medical Leave

Unlimited Paid Time Off

Paid Holidays

Monthly Wellness Stipend

Professional Development Budget

Mental Health Support

Employee Discounts

Adoption Assistance

Backup Child and Elder Care Program

Pre-tax Commuter Benefits

Employer-paid Group Term Life Insurance

Risks

Competition from tech giants like Tesla and Google may impact market share.

Continuous updates needed due to rapid AI advancements could be costly.

Consumer skepticism and regulatory hurdles may slow technology adoption.

Differentiation

Latitude AI combines startup agility with Ford's manufacturing excellence.

Focuses on hands-free, eyes-off driver assist systems for Ford vehicles.

Operates independently while serving millions of Ford customers.

Upsides

Increased investment in AI-driven automotive technologies boosts sensor fusion advancements.

V2X communication technologies enhance vehicle interaction with the environment.

Edge computing enables real-time data processing, improving automated driving performance.

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