Machine Learning Engineer

CMT is building DriveWell Atlas, a family of foundation models trained on large-scale, multi-modal telematics signals (e.g., inertial sensors, GPS-derived signals, device/context features) to power safer driving outcomes across risk, safety, crash and claims workflows. 

As an IC2 Foundation Models contributor, you will work closely with senior scientists and engineers to prototype, train, evaluate, and deploy time-series foundation models—while also helping optimize the underlying training/inference systems for scale and efficiency. This role is hands-on, highly technical, and well-suited for someone with strong software fundamentals and growing applied ML experience. 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.

Responsibilities: 

• Use independent judgment and discretion to develop ML / DL models which pattern driving behaviors and vehicle kinematics in data collected via smartphone sensors 
• Assist with projects and solutions through the full development stages, from data pre-processing, modeling, testing, through roll-out with minimum management oversight 
• Write code for debugging complex issues and creating new solutions that will run as part of production systems 
• Support customers’ requests regarding the production ML models and derive deep insights from data
• Use independent judgment and discretion to communicate and present data science work within the data science team as well as to stakeholders across the org and to collaborate across different teams 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Data Science, Computer Science, Statistics, Mathematics or Engineering 
• 2+ years of professional experience in the Data Science field 
• A good understanding of data science principles, algorithms and practices, such as machine learning, deep learning, statistics and probability 
• Knowledge of software development process, and proven coding skills using scripting languages e.g. Python, Pandas, NumPy, scikit-learn and SQL 
• Ability to write and navigate code, request data from data sources and code from scratch
• Experience with deep learning frameworks (TensorFlow, Keras, Torch, Caffe, etc.) and knowledge of Big Data infrastructure (Hadoop, Spark, etc.) will be a plus 
• A great team player and quick learner

Nice to haves:

• Experience with one or more of the following:
• • Time-series / sensor modeling (inertial signals, GPS-derived features, mobile/IoT data)
  • Distributed systems or big-data processing (streaming/batch pipelines; e.g., Kafka/Spark/Ray-style ecosystems)
  • GPU programming / performance optimization (CUDA, kernel-level efficiency, profiling/benchmarking, mixed precision training, and memory/performance tuning)
  • Model compression techniques (post-training quantization, pruning)
  • Demonstrated ability to translate ideas into working prototypes (course projects, research, prior roles).

Compensation and Benefits:

• Fair and competitive salary based on skills and experience, and annual performance bonus
• Equity may be awarded in the form of Restricted Stock Units (RSUs)
• Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave
• Unlimited Paid Time Off including vacation, sick days & public holidays
• Flexible scheduling and work from home policy depending on role and res