Self Driving

Self Driving Data Jobs

4 jobs found

1mo ago

Perception Machine Learning Engineer – ADAS

Lucid Motors Southfield, MI

Southfield, MI

1mo ago Closed

Full time Artificial Intelligence Automation Autonomous Vehicles

This position is no longer accepting applications (closed Sep 6, 2026).

Job Description

In this onsite role in Southfield, MI, you will develop and improve perception machine learning algorithms for autonomous driving systems. The work focuses on building deep learning models that leverage camera and LiDAR data and delivering them through testing and production deployment pipelines.

Responsibilities

Develop and optimize perception algorithms for autonomous driving systems using camera and LiDAR data.
Design and implement deep learning solutions for 2D and 3D object detection, segmentation, tracking, and multi-task learning.
Research and integrate BEV-based transformer models for perception tasks.
Collaborate with cross-functional teams to support seamless integration and robust implementation.
Test, release, and deploy perception algorithms into Lucid production programs.
Support validation and verification of perception algorithms using prototype and pre-production vehicles.
Propose software algorithm improvements to advance future autonomous driving capabilities.

Requirements

Strong theoretical foundation and expertise in deep learning algorithms, including object detection, tracking, and segmentation.
Proficiency in Python with a focus on clean, efficient, and scalable development.
Comfort working with large codebases and debugging complex machine learning models.
Experience with PyTorch or other ML frameworks such as TensorFlow or MXNet.
Ability to design and construct evaluation pipelines to unit-test ML models under diverse conditions and environments.
Excellent communication skills and strong teamwork.
Bachelor’s degree in Computer Engineering, Electrical Engineering, Automotive Engineering, Mechanical Engineering, or a related field.
Minimum 3 years of relevant work experience, or a Ph.D. in a related field for a senior position.

Technologies

Python
PyTorch
TensorFlow
MXNet
C++

Preferred Qualifications

Experience developing BEV transformer models for perception.
Proficiency in C++ with experience writing efficient, maintainable code.
Hands-on approach to solving complex autonomous driving problems.
Experience testing and validating perception systems in real-world conditions.
Experience working in agile development teams.
Expertise in component and system integration, testing, and verification at system and vehicle levels.

Benefits

Medical, dental, and vision insurance
Life and disability coverage
Paid time off
Paid holidays
401(k) retirement plan
Eligible employees may participate in Lucid’s equity program and/or a discretionary annual cash incentive program

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1mo ago

Senior Machine Learning Engineer, End‑to‑End Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

1mo ago Closed

$184k - $357k/yr Full time Senior Active Learning Artificial Intelligence

This position is no longer accepting applications (closed Aug 13, 2026).

Job Description

NVIDIA in Santa Clara is seeking a Senior Machine Learning Engineer to design, train, and deploy end-to-end autonomous driving models while building data-centric pipelines and data flywheels that accelerate development. This onsite role involves close collaboration with researchers and engineers to convert advanced research into robust, production-ready ML systems for autonomous vehicles.

Responsibilities

Design, implement, and train scalable end-to-end driving models for autonomous vehicles.
Drive the data flywheel by identifying failure modes, defining data collection and labeling needs, and iterating models to close real-world performance gaps.
Build, curate, and maintain high-quality multimodal datasets including video, sensor streams, and language/action traces for end-to-end driving.
Develop and apply data-centric learning strategies such as active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi/self-supervised methods.
Explore and productize new data sources, including simulation, synthetic data, and world-model-based generation or augmentation to improve coverage and robustness.
Design and implement automated data workflows that handle discovery, labeling, evaluation, and retraining to maximize development velocity.
Foster collaborative partnerships with researchers and engineers to transform innovative research into robust, production-ready ML models.

Requirements

PhD with 4+ years, MS with 6+ years, or BS (or equivalent) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related field.
Strong background in modern deep learning, including transformer architectures, video modeling, and multimodal VLM/VLA or foundation models.
Hands-on experience training and deploying deep learning models on real-world datasets, covering preprocessing, distributed training, evaluation, debugging, and iterative improvement.
Practical experience with data-centric methods such as active learning, curriculum learning, outlier/novelty detection, or large-scale sample mining.
Proficiency in Python and at least one major deep learning framework (PyTorch, TensorFlow, or JAX), plus solid software engineering practices (testing, code reviews, CI/CD).
Demonstrated ability to collaborate across teams, drive designs from prototype to production, and communicate with technical and non-technical partners.
Track record of leading complex cross-team projects, setting technical direction, and making critical technical decisions that impact multiple teams or products.

Technologies

Python
PyTorch
TensorFlow
JAX

Benefits

Equity
Benefits

Ways to stand out from the crowd

Experience building and operating data flywheels or large-scale data pipelines for ML, including data quality monitoring and continuous retraining loops.
Direct experience with end-to-end driving models, large-scale behavior cloning, or reinforcement/imitation learning for driving or robotics.
Experience leveraging simulation, synthetic data, or world models to generate training and evaluation data for autonomous systems.
Contributions to advanced data-centric ML methods, VLM/VLA, or autonomous driving through publications, open-source projects, or widely used internal tools.
Background with safety, reliability, and validation requirements for autonomous driving or other safety-critical applications.

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2mo ago

Machine Learning Engineer, Motion Planning & Prediction

Avride Austin, TX

Austin, TX

2mo ago Closed

Full time Ai Ml Artificial Intelligence Big Data

This position is no longer accepting applications (closed Jul 16, 2026).

Job Description

Avride is seeking a Machine Learning Engineer to join its autonomous vehicle team focused on motion planning and prediction in Austin, TX (onsite).

Responsibilities

Design, train, and deploy advanced ML models for behavioral prediction and motion planning.
Build robust data pipelines to process, clean, and label large-scale vehicle sensor and simulation datasets.
Leverage transformers and other deep learning architectures to capture temporal interactions among traffic agents.
Define and own model performance metrics; develop evaluation frameworks aligned with on-road safety and performance.
Collaborate with software engineers to integrate and optimize models for real-time on-vehicle embedded hardware inference.
Stay current with ML research, including imitation learning and reinforcement learning, and apply novel techniques to the systems.

Requirements

Strong Python skills and hands-on experience with modern deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Solid grounding in ML fundamentals, including neural network architectures, training methodologies, and evaluation techniques.
Experience across the ML lifecycle, from data exploration and prototyping to deployment and monitoring.
Proficiency in C++ for high-performance model inference code.

Technologies

Python
PyTorch
TensorFlow
JAX
C++
MLflow
Kubeflow
Weights & Biases
Spark
Ray

Nice to Have

Strong track record in ML competitions such as Kaggle or notable contributions to major open-source ML projects.
Experience applying ML to robotics problems like behavioral prediction, motion planning, or computer vision.
Experience with MLOps tools and platforms such as MLflow, Kubeflow, Weights & Biases.
Experience with large-scale distributed data processing and training frameworks such as Spark or Ray.
Publications in top ML or robotics conferences (e.g., NeurIPS, ICML, CVPR, ICLR, CoRL, RSS).

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3mo ago

Machine Learning Engineer, Destination & Special Behaviors, Self-Driving

Tesla Palo Alto, CA

Palo Alto, CA

3mo ago Closed

$176k - $420k/yr Full time Artificial Intelligence Deep Learning Machine Learning

This position is no longer accepting applications (closed Jun 18, 2026).

Job Description

Tesla is seeking an experienced applied Machine Learning Engineer to help build robust end-to-end learning-based self-driving models for robotics and vehicle autonomy, onsite in Palo Alto, CA.

Responsibilities

Develop novel techniques to robustly manage start-of-trip and end-of-trip Robotaxi behaviors at scale
Leverage millions of miles of driving data and interventions to build a robust, scalable end-to-end learning-based self-driving system
Apply cutting-edge methods from generative modeling, imitation learning, and reinforcement learning to improve planning and reasoning for driving models
Collaborate across ground-truth generation, ML model training, and on-vehicle deployment
Experiment with data generation and fleet data collection to enhance training data diversity and quality
Integrate production-grade, safety-critical software with vehicle firmware for deployment across Tesla's fleet

Requirements

Strong experience with Python, any major deep learning framework, and software engineering best practices
In-depth knowledge of modern deep learning architectures, optimization techniques, and model alignment
Proven experience deploying production ML models for self-driving and robotics at scale
Experience with C++ is a plus for vehicle firmware integration and shipping projects

Technologies

Python
C++

Benefits

Medical plans with plan options that involve no employee payroll deductions
Family-building, fertility assistance, adoption and surrogacy benefits
Dental and vision coverage with options that require zero after-tax contributions
Company paid Health Savings Account contributions when enrolled in a high deductible medical plan with an HSA
Healthcare and Dependent Care Flexible Spending Accounts (FSA)
401(k) with employer match, Employee Stock Purchase Plan, and other financial benefits
Company paid Basic Life and AD&D insurance
Short-term and long-term disability insurance (90 day waiting period)
Employee Assistance Program
Sick and vacation time, paid holidays, and flexible scheduling for salaried roles with accrued hours for hourly positions
Back-up childcare and parenting support resources
Voluntary benefits including critical illness, hospital indemnity, accident insurance, theft and legal services, and pet insurance
Weight loss and tobacco cessation programs
Tesla Babies program
Commuter benefits and employee discounts and perks program

What to expect

Tesla seeks an experienced applied ML engineer to build models that deliver robust robotics-enabled autonomy across current and future vehicle generations. You will work on a lean team with few boundaries and have access to one of the world’s largest training clusters; your work will be shipped to and used by millions of Tesla customers.

Expected compensation

Salary range: USD 176,000 - 420,000 per year, plus cash and stock awards and benefits
Pay may vary based on location, job-related knowledge, skills, and experience; total compensation may include additional elements
Details about participation in benefit plans will be provided if an employment offer is extended

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Self Driving Data Jobs

Perception Machine Learning Engineer – ADAS

Senior Machine Learning Engineer, End‑to‑End Autonomous Driving

Machine Learning Engineer, Motion Planning & Prediction

Machine Learning Engineer, Destination & Special Behaviors, Self-Driving

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