Mobile Machine Learning Jobs in Boston, MA (NOW HIRING)

Job Summary:
Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. As a Principal Machine Learning Engineer on the DriveWell Atlas team, you will lead the development of next-generation AIs focused on telematics data to enhance risk assessment and driver engagement.
Responsibilities:
• 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
Qualifications:
Required:
• 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, GCP, 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
Preferred:
• 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
Company:
Cambridge Mobile Telematics develops DriveWell, a complete telematics and behavioral analytics solution to improve safety. Founded in 2010, the company is headquartered in Cambridge, USA, with a team of 201-500 employees. The company is currently Growth Stage.