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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, Amazon Elastic Compute Cloud, Amazon S3, Microsoft Azure, Big Data, C++ (Programming Language), Database Queries, Python (Programming Language), Machine Learning, Scala (Programming Language), Sensor Fusion, Software Engineering, Apache Spark, Deep Learning, Kubernetes, Information Technology, Apache Kafka, Machine Learning Operations, Functional Programming, Docker, Programming Languages
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=79c575e1db26a7fc

## About the Role

* Master's degree or equivalent years of experience and/or certification in Data Science, Computer Science, Electrical Engineering, Physics, or Mathematics
 * 7+ years of professional experience in AI/ML
 * 3+ years of hands-on experience developing and deploying deep learning models with a strong portfolio in generative AI for sequential or spatio-temporal data
 * Strong software engineering skills in Python
 * Must have at least two years of AWS experience and demonstrated knowledge of common AWS services such as EC2, S3, Lambda, Athena, Redshift, etc
 * Must have at least 2 years of professional experience with computer languages such as Python, C++, Scala, etc
 * Strong knowledge of SQL concepts, ability to comprehend and write complex SQL statements
 * Excellent problem solving, communication, and cross-functional collaboration

Nice to Haves:

 * Ph.D. in a relevant field.
 * Hands-on experience with time-series or multi-modal architectures for sensor fusion and behavioral modeling
 * Background in self-supervised learning on real-world sensor data and physics-informed modeling
 * Experience building large-scale data processing and orchestration: Spark or Beam, Airflow, Kafka or Pub/Sub, Docker, and Kubernetes on AWS, GCP, or Azure
 * Publications in strong AI or ML venues



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