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# Principal Machine Learning Engineer

- **Company:** Cambridge Mobile Telematics
- **Location:** Cambridge, MA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $177,000.0 - $221,300.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Distributed Computing Environment, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Sensor Fusion, Google Cloud, Pytorch, Apache Spark, Deep Learning, Pandas, Scikit Learn, Information Technology, Machine Learning Operations, Docker
- **Published:** June 24, 2026
- **Apply:** https://www.dice.com/job-detail/79f7b126-4113-4adb-88eb-32567f959018

## About the Role

* Bachelor's degree or equivalent years of experience and/or certification in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a related field
 * 7+ years of professional experience in AI/ML
 * 3+ years of hands-on experience developing and deploying foundation models, with a strong portfolio in generative AI for sequential or spatio-temporal data
 * Strong, hands-on experience in building and training time-series transformer architectures for complex sensor fusion and behavioral modeling tasks is required
 * Deep expertise in designing pretraining tasks for self-supervised learning on noisy, real-world sensor data
 * Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn)
 * Extensive experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow for large-scale model training and deployment
 * Solid understanding and practical experience with distributed training techniques and efficient training methodologies for large models
 * Experience building and maintaining large-scale data processing pipelines and machine learning infrastructure using tools like Spark, Airflow, Docker, and cloud platforms (e.g., AWS, Google Cloud Platform, Azure)
 * Excellent problem-solving skills and the ability to translate complex business problems into tractable AI-based solutions
 * Strong verbal/written communication and collaboration skills, with the ability to effectively convey complex technical concepts to diverse audiences
 * Product-focused thinking with a proven ability to deliver impactful AI solutions

Nice to Haves:

 * PhD or Master's degree preferred
 * Experience with MLOps practices and tools for managing the lifecycle of machine learning models
 * Publications in top-tier AI/ML conferences or journals
 * Familiarity with techniques for model interpretability and explainability (XAI)
 * Awareness of ethical AI principles, bias detection, and mitigation strategies in machine learning models, including experience with or understanding of model guardrails

## Description

* Use independent judgment and discretion to lead the design, pre-training, fine-tuning, and deployment of novel foundation models for vehicle telematics
 * Develop and implement novel algorithms for modeling both automotive physics and human driving behavior
 * Pioneer advanced self-supervised learning techniques, including the design and implementation of innovative tasks tailored to multi-modal telematics sensor data to learn rich representations of movement and driver behavior
 * Develop models robust to noise, missing data, and diverse operating conditions typical of real-world mobile sensor and IoT datasets
 * Build and manage scalable training and inference pipelines using tools like Ray, PyTorch DDP, Horovod, or similar frameworks
 * Integrate these AIs into production systems while ensuring high performance and reliability
 * Optimize these AIs for efficient deployment on various platforms, including cloud and edge/mobile devices
 * Collaborate closely with engineering, product, and research teams to translate cutting-edge research into impactful products and features for the DriveWell Atlas platform
 * Mentor junior scientists and contribute to the broader AI/ML strategy at CMT
 * Stay abreast of the latest AI advancements, evaluating and adopting emerging technologies and methodologies relevant to telematics
 * Contribute to efforts in AI explainability and interpretability
 * Complete any tasks as they arise


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