Senior Machine Learning Engineer (End-to-End Driving)

At 42dot, our Senior Machine Learning Engineer team focuses on developing state-of-the-art solutions in Motion Planning algorithms. We create advanced prediction algorithms for future path planning, a critical aspect of ensuring the safety and reliability of autonomous driving systems. By utilizing vast datasets, we conduct comprehensive analyses of driving patterns, allowing us to design algorithms that facilitate smooth and natural vehicle control. Our goal is to drive the innovation needed to shape the future of autonomous driving technologies.

Responsibilities

• Lead the design and development of advanced machine learning models for autonomous driving tasks, including perception, decision-making, and control

• Drive end-to-end machine learning pipeline development from data collection and preprocessing to model training, optimization, and deployment

• Apply state-of-the-art deep learning techniques, such as reinforcement learning, imitation learning, and self-supervised learning, to improve autonomous driving performance

• Optimize model performance in real-world driving conditions and ensure seamless integration with the vehicle’s software stack

• Collaborate with cross-functional teams, including software, hardware, and vehicle control, to align machine learning systems with overall vehicle architecture

• Mentor junior engineers and guide best practices for machine learning development

• Stay updated on the latest trends and research in machine learning and autonomous driving, bringing innovative approaches to the team

Qualifications

• Master’s or Ph.D. in Computer Science, Machine Learning, AI, Robotics, or a related field

• Extensive experience with deep learning algorithms (CNN, RNN, Transformer) and their applications in autonomous systems

• Strong proficiency in Python and machine learning frameworks (TensorFlow, PyTorch), with a proven track record of deploying models in real-world systems

• Deep understanding of reinforcement learning, imitation learning, and advanced optimization techniques

• Experience working with large-scale datasets and cloud-based machine learning pipelines

• Excellent leadership and communication skills, with a demonstrated ability to lead technical projects

Preferred Qualifications

• Strong background in autonomous driving technologies and end-to-end learning for self-driving cars

• Experience with hardware-in-the-loop (HIL) testing and real-time deployment

• Experience in research and development related to autonomous driving and robotics

• ROS1/ROS2 experience

• Experience deploying predictive models in real-world environments

• Inference optimization experience (TensorRT, CUDA programming, etc.)

• History of books/academic activities in related fields (CVPR, ICCV, ECCV, IROS, ICRA, etc.)

Interview Process

• Application Review - 1st interview - 2nd interview - 3rd interview - Offer Negotiation - Hiring

• Screening procedures may be operated differently for each job and may vary depending on the schedule and situation.

• The screening schedule and results will be notified individually by email registered on the application form.

Additional Information

• In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.

• All documents must be submitted in PDF format and under 30MB in size.

•  If you experience issues uploading your resume, please send it along with the job posting URL to [email protected].

• We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.

• Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).

• 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement

• 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

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