Summer 2023: Machine Learning Intern

Pittsburgh, Pennsylvania, United States

Applications have closed

Motional

Motional harnesses deep industry experience in our mission to develop and deploy autonomous vehicles and to make driverless technology safe and reliable.

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Machine Learning Intern 

At Motional, we believe in Data Science and Artificial Intelligence: they are the pillars of our world-class, machine learning-based, autonomous driving stack. By joining the Data Mining team, you will directly contribute to making roads safer, by helping us harness the potential of our collection of hundreds of hours of driving scenarios.

In particular, you will participate in the improvement of our perception & prediction stack, by identifying rare and challenging driving scenarios for our prediction models. You will develop automated workflows for mining vast real-world data from our on-road vehicle fleet and integrate them to our Search Engine to be used for data discovery and model training.

What you'll be doing:

  • Prototype and deploy ML products that utilize techniques such as few-shot learning and metric learning in collaboration with cross-functional teams.
  • Develop mining workflows and integrate them to our Search Engine to allow the discovery of long-tail vehicle trajectories that are informative to the Perception & Prediction stack.
  • Improve the performance of prediction and planning models through the utilization of rare and challenging vehicle trajectories (e.g. u-turn and 3-point-turn).
  • Contribute to the creation of patents and scientific publications by developing innovative machine learning learning solutions.

What we're looking for:

  • Currently pursuing or recently completed a Master's or Ph.D. degree in Computer Science, Applied Mathematics, Statistics, Robotics or related fields.
  • Proficiency and practical experience with Python and relevant machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Experience applying at least one of the following ML techniques: Few-shot Learning, Metric Learning, Information Retrieval, Recommender Systems, Object Detection/Segmentation/Prediction.
  • Self-motivated, hands-on, desire to work in a fast-paced environment.

Bonus Points:

  • Experience working with large-scale datasets, distributed systems, and cloud computing.
  • Familiarity with cutting-edge models like transformer-based architectures for multimodal learning is a plus.
  • Experience with writing high quality and maintainable code.
  • Experience with software development best practices, including version control, code review, and testing.
  • Knowledge of autonomous vehicle technology and familiarity with the autonomous vehicle industry.

If you don’t meet 100% of the qualifications outlined above - that’s okay! We encourage you to apply if you think this is a role that would make you excited to come into work every day and that you can deliver the results we need.

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. 

Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Salary Range$35—$55 USD

Motional is a driverless technology company making self-driving vehicles a safe, reliable, and accessible reality.

The Motional team is made up of engineers, researchers, innovators, dreamers and doers, who together are creating a first-of-its-kind technology with the potential to transform the way we move. We’re behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's most-established public robotaxi fleet.

As a leader in an emerging industry that has the promise of creating safer, more reliable and accessible transportation for all, it’s imperative we have a diverse workforce, create an inclusive culture, and understand the communities we operate in around the world. 

Diversity, Equity and Inclusion is fundamental to Motional’s success. That’s why we’ve established a team to ensure DEI is at the forefront of the candidate and employee experience, beginning with the hiring process and continuing throughout your career. We also partner with organizations like the National Society of Black Engineers, the Society of Hispanic Professional Engineers, and the Society of Women Engineers to ensure our DEI work is informed by the latest thinking and approaches.

Strategically formed by Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit  www.Motional.com and follow us on Twitter, LinkedIn, Facebook, Instagram and YouTube.

 

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

Tags: Architecture Autonomous Driving Computer Science Data Mining Distributed Systems Machine Learning Mathematics Model training Python PyTorch Recommender systems Robotics Statistics TensorFlow Testing

Perks/benefits: 401(k) matching Career development Equity Health care Salary bonus

Region: North America
Country: United States
Job stats:  263  184  2

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