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Machine Learning Engineer, Autonomous Vehicles

Job Title: Machine Learning Engineer - Foundation Models & Generative Driving Scenarios

Salary: $175-200K annually

**MUST BE US BASED**

The Prediction & Behavior ML team is responsible for developing machine learning (ML)
algorithms that learn and predict behaviors from data, applying them both on-vehicle to
influence driving behavior and off-vehicle to provide ML capabilities to simulation and
validation. Given the tight integration of behavior forecasting and motion planning, our
team collaborates closely with the Planner team to advance overall vehicle behavior.
We also work closely with our Perception, Simulation, and Systems Engineering teams
to accelerate our ability to validate our driving performance.

As an engineer working on Foundation Models and Generative Driving Scenarios, you
will be responsible for developing advanced ML models that can serve as the
foundation for various prediction and generation tasks within our autonomous driving
systems.

In this role, you will:
● You will build multimodal foundation models that can be used as the
backbone for a variety of ML tasks within the autonomous driving
domain.
● You will develop new algorithms to apply these foundation models to
generate realistic and diverse driving scenarios for our offline simulation
and validation systems, improving the fidelity and diversity of our testing
environment.
● You will leverage our large-scale machine learning infrastructure to
discover new solutions and push the boundaries of the field.
● You will collaborate with engineers on Perception, Planning, and
Simulation to solve the overall Autonomous Driving problem in complex
urban environments.

Qualifications
● BS, MS, or PhD degree in computer science or related field
● Experience with training and deploying Deep Learning models
● Experience with production Machine Learning pipelines: dataset
creation, training frameworks, metrics pipelines
● Fluency in C++ or Fluency in Python with a basic understanding of C++
● Extensive experience with programming and algorithm design
● Strong mathematics skills

Bonus Qualifications
● Conference or Journal publications in Machine Learning or Robotics
related venues
● Prior experience with Prediction and/or autonomous vehicles or robotics
in general
● Experience with training / fine-tuning multimodal foundation models
● Experience with training and evaluating generative models
● Experience with Reinforcement Learning

  • Health Care Plan (Medical, Dental & Vision)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Training & Development
  • Retirement Plan (401k, IRA)

Average salary estimate

$187500 / YEARLY (est.)
min
max
$175000K
$200000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Machine Learning Engineer, Autonomous Vehicles, A Society Group, Inc.

Welcome to an exciting opportunity at our company, where we are looking for a passionate Machine Learning Engineer specializing in Autonomous Vehicles to join our Prediction & Behavior ML team. In this pivotal role, you will be developing cutting-edge machine learning algorithms that can learn and predict vehicle behaviors from data, significantly enhancing both on-vehicle driving behavior and providing unparalleled machine learning capabilities to our simulation and validation efforts. As a Machine Learning Engineer focusing on Foundation Models and Generative Driving Scenarios, you will create advanced models that will serve as the backbone of our autonomous driving systems. Your work will involve building multimodal foundation models and developing innovative algorithms to generate diverse and realistic driving scenarios, critical for offline simulation. You will collaborate with a talented team of engineers from various departments, including Perception, Planning, and Simulation, all aimed at solving the big challenges of Autonomous Driving in dynamic urban settings. Our ideal candidate holds a BS, MS, or PhD in computer science or a related field, with experience in deploying Deep Learning models and a firm grasp of programming languages, particularly C++ and Python. If you thrive in a fast-paced environment and are eager to push the boundaries of predictive models in autonomous vehicles, we want to hear from you!

Frequently Asked Questions (FAQs) for Machine Learning Engineer, Autonomous Vehicles Role at A Society Group, Inc.
What responsibilities does a Machine Learning Engineer at our company have?

The Machine Learning Engineer at our company plays a vital role in developing advanced machine learning algorithms to predict vehicle behaviors. This involves building multimodal foundation models, creating diverse driving scenarios for simulation use, and collaborating with cross-functional teams to enhance autonomous driving capabilities.

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What qualifications are needed for the Machine Learning Engineer position in Autonomous Vehicles?

To apply for the Machine Learning Engineer position, candidates should possess a BS, MS, or Ph.D. in computer science or a related field. Experience with deploying Deep Learning models, understanding machine learning pipelines, and proficiency in programming languages like C++ or Python is crucial.

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Is prior experience in autonomous vehicles necessary for this Machine Learning Engineer role?

While prior experience with autonomous vehicles is a bonus for the Machine Learning Engineer position, it is not strictly necessary. However, familiarity with prediction models and robotics will certainly enhance a candidate's application.

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How can a Machine Learning Engineer contribute to validation processes in our company?

A Machine Learning Engineer can significantly enhance validation processes by developing algorithms that generate realistic and diverse driving scenarios, thus improving the fidelity of simulations. This collaboration ensures that the autonomous driving systems are rigorously tested under a variety of conditions.

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What soft skills are important for a Machine Learning Engineer working on autonomous vehicles?

In addition to technical skills, a Machine Learning Engineer should possess strong collaboration and communication skills, as the role involves working closely with various teams. Being adaptable and innovative will also help in finding creative solutions to complex problems in the autonomous driving domain.

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Common Interview Questions for Machine Learning Engineer, Autonomous Vehicles
Can you explain your experience with deep learning models?

When answering this, provide specific examples of deep learning projects you've worked on, the frameworks you used, and the results achieved. Highlight your familiarity with training and deploying these models effectively.

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What role does collaboration play in your work as a Machine Learning Engineer?

Discuss the importance of teamwork in developing machine learning systems, emphasizing how you've worked with cross-functional teams to achieve common goals, such as enhancing system capabilities or addressing challenges.

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How do you approach model evaluation and validation?

Share your methods for assessing model performance, including metrics you prioritize. Discuss any structured processes you follow to ensure the reliability of the models you develop.

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Tell me about a challenging machine learning problem you've solved.

When discussing a challenge, detail the problem, the approach you took to address it, and the end results. Emphasize what you learned and how this experience has shaped your understanding of machine learning in autonomous driving.

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What programming languages are you most comfortable with and why?

Express your proficiency in required languages, like Python and C++. Discuss specific projects where you applied these skills, emphasizing how they were integral to achieving project objectives.

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How do you stay up-to-date with advancements in machine learning?

Explain your commitment to continuous learning, such as following academic journals, participating in conferences, and engaging with online courses or webinars to keep your skills sharp in the rapidly evolving field.

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Can you provide an example of how you've implemented feedback in your work?

Share an instance where feedback led to significant improvements in your projects. Discuss how this collaborative approach contributed to a better outcome.

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What techniques do you use to build diverse driving scenarios?

Discuss the various algorithms and modeling techniques you apply to create varied scenarios, emphasizing the importance of diversity in testing and validation for robust autonomous systems.

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How do you handle tight deadlines in your projects?

Describe your strategies for managing time effectively under pressure, such as prioritization techniques, communication with stakeholders, or tools you utilize to maintain productivity.

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What makes you passionate about autonomous vehicles?

Convey your genuine interest by discussing personal motivations, experiences, or ideas related to the future of transportation and the role of machine learning in enhancing safety and efficiency in autonomous systems.

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A Society is a modern consulting company that gives self-employed consultants access to the most exciting and developing assignments. Future generations of workforce prioritises freedom and with basic... security and a strong sense of belonging th...

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Full-time, remote
DATE POSTED
April 8, 2025

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