We are embarking on a transformative journey with DriveWell Atlas, a groundbreaking initiative to build a family of novel AIs on telematics data. As a Principal Machine Learning Engineer on the DriveWell Atlas team, you will be at the forefront of developing these next-generation AIs. You will lead innovative projects focused on designing, pre-training, fine-tuning, and deploying these AIs. 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. We are not tweaking existing models for marginal gain. You will have an opportunity to build a first-of-its-kind LLM from petabyte-scale data.<br><br>CMT is looking for a <strong>Principal Machine Learning Engineer, Foundation Models </strong>to help us change the world. CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.<br><br><strong>Responsibilities:</strong> <br><br><ul><li>Use independent judgment and discretion to lead the design, pre-training, fine-tuning, and deployment of novel foundation models for vehicle telematics </li><li>Develop and implement novel algorithms for modeling both automotive physics and human driving behavior </li><li>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 </li><li>Develop models robust to noise, missing data, and diverse operating conditions typical of real-world mobile sensor and IoT datasets </li><li>Build and manage scalable training and inference pipelines using tools like Ray, PyTorch DDP, Horovod, or similar frameworks </li><li>Integrate these AIs into production systems while ensuring high performance and reliability</li><li>Optimize these AIs for efficient deployment on various platforms, including cloud and edge/mobile devices </li><li>Collaborate closely with engineering, product, and research teams to translate cutting-edge research into impactful products and features for the DriveWell Atlas platform </li><li>Mentor junior scientists and contribute to the broader AI/ML strategy at CMT </li><li>Stay abreast of the latest AI advancements, evaluating and adopting emerging technologies and methodologies relevant to telematics </li><li>Contribute to efforts in AI explainability and interpretability </li><li>Complete any tasks as they arise<br><br></li></ul><strong>Qualifications:</strong> <br><br><ul><li>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 </li><li>7+ years of professional experience in AI/ML </li><li>3+ years of hands-on experience developing and deploying foundation models, with a strong portfolio in generative AI for sequential or spatio-temporal data </li><li>Strong, hands-on experience in building and training time-series transformer architectures for complex sensor fusion and behavioral modeling tasks is required </li><li>Deep expertise in designing pretraining tasks for self-supervised learning on noisy, real-world sensor data </li><li>Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn)</li><li>Extensive experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow for large-scale model training and deployment </li><li>Solid understanding and practical experience with distributed training techniques and efficient training methodologies for large models </li><li>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)</li><li>Excellent problem-solving skills and the ability to translate complex business problems into tractable AI-based solutions </li><li>Strong verbal/written communication and collaboration skills, with the ability to effectively convey complex technical concepts to diverse audiences </li><li>Product-focused thinking with a proven ability to deliver impactful AI solutions<br><br></li></ul><strong>Nice to Haves:</strong> <br><br><ul><li>PhD or Master's degree preferred </li><li>Experience with MLOps practices and tools for managing the lifecycle of machine learning models</li><li>Publications in top-tier AI/ML conferences or journals </li><li>Familiarity with techniques for model interpretability and explainability (XAI) </li><li>Awareness of ethical AI principles, bias detection, and mitigation strategies in machine learning models, including experience with or understanding of model guardrails<br><br></li></ul><strong>Compensation and Benefits:<br><br></strong><ul><li> Fair and competitive salary based on skills and experience, and annual performance bonus</li><li>Equity may be awarded in the form of Restricted Stock Units (RSUs)</li><li>Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave</li><li>Unlimited Paid Time Off including vacation, sick days & public holidays</li><li>Flexible scheduling and work from home policy depending on role and responsibilities<br><br></li></ul><strong>Base Salary Range<br><br></strong><ul><li>The base salary range for this position is: $177,000 to $221,300. This range is specifically for Cambridge, MA<br><br></li></ul><strong>Additional Perks:<br><br></strong><ul><li>Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world</li><li>Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries</li><li>Be part of the team inventing the future of mobility and road safety</li><li>Move fast, own outcomes, do work that matters</li><li>High ownership, small teams, and direct access to leadership — no layers between your work and its impact</li><li>Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match</li><li>Summer Fridays</li><li>Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness</li><li>Comprehensive wellness, education, and employee assistance programs<br><br></li></ul><strong>Commitment to Diversity and Inclusion:<br><br></strong><strong>At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. <br><br></strong><strong>We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. <br><br></strong><em>We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.<br><br></em><strong>About Cambridge Mobile Telematics:<br><br></strong>Cambridge Mobile Telematics (CMT) is the world's largest telematics and AI company for safer mobility. Its mission is to make the world's roads and drivers safer. The company's AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT's technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.