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Machine Learning Engineer, Data Mining

Motional -
Boston, MA

Quick Apply

Job Details

$144,000 - $192,000 a year
11 days ago

Qualifications

AI models
Software coding
Software deployment
AI platforms (beyond public GPTs)
Computational framework
SQL
Machine intelligence
Model deployment
Version control systems
Developing large-scale AI models
Model training
Unit testing
Machine learning libraries
Model evaluation
Machine learning frameworks
Design (software development lifecycle)
Feature engineering
Statistical analysis tools
Database software proficiency

Full Job Description

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional's driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval.
Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments.
Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios.
Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services.
Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation.
Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions.

What We're Looking For (Must-Haves):

BS or MS in Computer Science, Machine Learning, or a related field.
Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics.
Strong proficiency in Python with the ability to write clean, modular, and well-documented code.
Working knowledge of version control, unit testing, and basic software design patterns.
Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy.
A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics.
A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment.

Bonus Points (Nice-to-Haves):

MS/PhD in Computer Science, Machine Learning, or related field.
Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
Background in autonomous driving, robotics, or real-time decision-making systems.
Familiarity with multimodal learning, sensor fusion, or embodied AI.
Experience building active learning loops, using the model to find the data that breaks the model.
Experience with ML-based data mining, active learning, or contrastive learning.
Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV)

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.

Our journey is always people first.

We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.

Higher purpose, greater impact.

We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.

Scale up, not starting up.

Our team is 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 longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.

Formed as a joint venture between 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, 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.

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