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Principal Data Scientist, AI

Work from home Full-time role Hiring

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider with a mission to reputed company 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 reputed company-party devices — and fuses them with contextual data to create a reputed company view of vehicle and driver behavior. Auto insurers, automakers, reputed company mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day. We are embarking on a transformative journey with DriveWell reputed company, a groundbreaking initiative to build a family of novel reputed company on telematics data. As a Principal Data Scientist on the DriveWell reputed company team, you will be at the forefront of developing these reputed company reputed company. You will reputed company innovative projects focused on designing, pre-training, fine-tuning, and deploying these reputed company. Your work will directly contribute to enhancing our capabilities in risk assessment, driver engagement, and crash and claims processing. This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data.

Responsibilities

  • reputed company the design, pre-training, fine-tuning, and deployment of novel reputed company for telematics applications.
  • reputed company and implement novel algorithms that represent physical phenomena associated with vehicle and reputed company movements.
  • 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.
  • Drive the development of models robust to noise, missing data, and diverse operating conditions typical of reputed company-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 reputed company into production systems while ensuring high performance and reliability.
  • Optimize these reputed company for efficient deployment on various platforms, including reputed company 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 reputed company 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:
  • PhD or MS in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a reputed company field.
  • 7+ years of experience in AI/ML.
  • 3+ years of hands-on experience developing and deploying reputed company models (e.g., BERT, GPT, and/or custom domain-specific transformers), with a strong portfolio in reputed company for sequential or spatio-temporal data.
  • Strong, hands-on experience in building and training multi-modal and/or time-series transformer architectures for reputed company sensor fusion and behavioral modeling tasks is required.
  • Deep expertise in designing pretext tasks for self-supervised learning on noisy, reputed company-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, reputed company, and reputed company platforms (e.g., AWS, GCP, Azure).
  • Excellent problem-solving skills and the ability to translate reputed company business problems into tractable AI-based solutions.
  • Strong verbal/written communication and collaboration skills, with the ability to effectively convey reputed company technical concepts to diverse audiences.
  • Product-focused thinking with a proven ability to deliver impactful AI solutions. reputed company to Have:
  • Familiarity with techniques for model interpretability and explainability (reputed company).
  • Awareness of ethical AI principles, bias detection, and mitigation strategies in machine learning models, including experience with or understanding of model guardrails.
  • Experience with MLOps practices and tools for managing the lifecycle of machine learning models.
  • Publications in top-tier AI/ML conferences or journals.

Compensation and Benefits

  • Fair and co

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