Senior Deep Learning Engineer (Navigation)

Outrider; United States; Remote; USD 155,000 - 220,000; Full time

Job summary

A leading company in autonomous freight systems seeks a Senior ML/Deep Learning Engineer to lead the development of their ML stack for navigation. You will create and deploy deep learning models to enhance the capabilities of self-driving trucks, working alongside a high-performing team. This role involves developing robust tooling, mentoring engineers, and maintaining high software standards, all while contributing to a production-grade autonomous solution.

Benefits

Full health benefits

Home office stipend up to $500

Qualifications

• 4+ years of hands-on experience developing and deploying deep learning models.
• Proficiency with modern ML/DL frameworks.

Responsibilities

• Develop and train models for applications such as path planning and scene understanding.
• Integrate ML models into production-vehicle systems.

Skills

Deep Learning

Machine Learning

Communication

Education

Bachelor’s or Master’s degree in Computer Science

Tools

PyTorch

TensorFlow

NumPy

Scikit

Job description

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The Company

Outrider is automating distribution yards using electric, self-driving trucks. Our system replaces hazardous, repetitive tasks to improve safety, efficiency, and sustainability in freight operations. Founded in 2018, we are a private company backed by NEA, 8VC, Koch Disruptive Technologies, NVIDIA, and other top-tier investors. Our autonomous systems are already deployed with Fortune 200 customers. Learn more at www.outrider.ai.

At Outrider, you’ll help build and deploy cutting-edge software that powers the next generation of autonomous freight systems. Your work will have direct, real-world impact—improving safety, precision, and sustainability across the global supply chain. You'll collaborate with top engineers across autonomy, robotics, and infrastructure to build reliable, scalable systems that keep goods moving.

The Role

We are looking for a Senior ML/Deep Learning Engineer to lead the development of our ML stack for navigation. This role centers on creating and deploying deep learning models that enable our autonomous trucks to navigate complex, dynamic environments such as distribution yards.

This is not a generic AV problem—we work in a constrained but highly demanding domain, with custom electric vehicles, purpose-built hardware, and real customers. You'll work alongside a focused, high-performing team and leadership that is committed to delivering a production-grade autonomous solution.

Duties & Responsibilities

• Work closely with the other teams in Autonomy, including data, ML, and integration, to:

• Develop and train models for applications such as path planning, behavioral planning, and scene understanding
• Evaluate model performance
• Incorporate models into navigation algorithms
• Integrate ML models into production-vehicle systems
• Define and manage datasets across various operational conditions and customer sites
• Be responsible for the full software engineering lifecycle: requirements, design, source code implementation, unit test, integration, and system test
• Drive tasks of rapid iteration of dataset generation, model training, evaluation and new development work to fix problems observed, repeat
• Develop robust tooling and infrastructure to support scalable ML development and model integration
• Maintain high software engineering standards with well-documented, tested, and modular code
• Mentor and collaborate with engineers to foster a high-performance, learning-focused culture

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Robotics, or a related field
• 4+ years of hands-on experience developing and deploying deep learning models in production settings
• Proficiency with modern ML/DL frameworks such as PyTorch, TensorFlow, NumPy, and Scikit
• Familiarity with recent research and state-of-the-art practices in deep learning
• Deep understanding of ML model design, training, evaluation, and debugging
• Strong communication skills with the ability to collaborate cross-functionally

Ideal Qualifications

• Strong understanding of robotics, navigation, localization, or autonomous systems
• Proficiency in reinforcement learning for motion planning or control
• Prior experience in fast-paced startup or research-driven environments

Compensation & Benefits

• Salary: $155,000 - $220,000
• Equity: Significant equity package commensurate on experience and skills
• Benefits: Full health benefits
• Fully remote, with opportunities to travel to our Denver headquarters for collaborations and events
• Home office stipend up to $500
• Actual compensation based on skills, experience, and location