Principal Data Scientist, AI

Job Description

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider, with a mission to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior.

CMT is embarking on a transformative journey with DriveWell Atlas, a groundbreaking initiative to build a family of novel AIs on telematics data. As a Principal Data Scientist, you will lead the development of next-generation AI models for risk assessment, safety, crash detection, and claims processing.

Responsibilities:

• Lead the design, pre-training, fine-tuning, and deployment of novel AIs for telematics applications.

• Develop algorithms that represent physical phenomena associated with vehicle and human movements.

• Design advanced self-supervised learning tasks for multi-modal telematics sensor data.

• Build robust models for noisy, missing, and diverse real-world data.

• Manage scalable training and inference pipelines using frameworks such as PyTorch DDP, Ray, or Horovod.

• Integrate AIs into production systems while ensuring performance and reliability.

• Optimize deployment across cloud and edge/mobile platforms.

• Collaborate with engineering, product, and research teams.

• Mentor junior scientists and contribute to the broader AI/ML strategy.

• Contribute to AI explainability and interpretability initiatives.

Qualifications:

• PhD or MS in AI, Computer Science, Electrical Engineering, Physics, Mathematics, or related field.

• 7+ years of experience in AI/ML.

• 3+ years of experience developing and deploying foundation models (BERT, GPT, or domain-specific transformers).

• Expertise in time-series and multi-modal transformer architectures.

• Strong background in self-supervised learning for noisy sensor data.

• Proficiency in Python and ML libraries (NumPy, Pandas, scikit-learn).

• Deep learning expertise with PyTorch (preferred) or TensorFlow.

• Experience with distributed training, ML infrastructure, and cloud platforms (AWS, GCP, Azure).

• Strong communication and problem-solving skills.

Nice to Have:

• Knowledge of model interpretability and explainability (XAI).

• Understanding of ethical AI and bias mitigation strategies.

• Familiarity with MLOps practices and tools.

• Publications in top-tier AI/ML conferences or journals.

Compensation & Benefits:

• Competitive salary (based on experience)

• Annual performance bonus

• Equity opportunities (RSUs)

• Medical, Dental, Vision, and Life Insurance

• 401(k) matching

• Unlimited Paid Time Off (vacation, sick days, public holidays)

• Flexible scheduling & hybrid work policy

• Wellness, education, and employee assistance programs