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cambridgemobiletelematics
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США
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123 000 $ – 153 700 $
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Machine Learning Engineer

Оценка ИИ

Отличная позиция в лидирующей компании сектора телематики с прозрачной вилкой зарплаты и RSU. Интересные задачи на стыке IoT и Foundation Models, а также сильный социальный пакет делают вакансию крайне привлекательной.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует сильных навыков программирования и опыта работы с глубоким обучением. Работа с временными рядами и фундаментальными моделями (Foundation Models) подразумевает высокий уровень математической подготовки и владение современными ML-фреймворками.

Анализ зарплаты

Медиана145 000 $
Рынок120 000 $ – 170 000 $
Оценка ИИ

Предложенная вилка $123k–$153k полностью соответствует рыночным стандартам для ML-инженеров уровня Middle в Кембридже, штат Массачусетс. С учетом бонусов и акций (RSU) совокупный доход может быть значительно выше среднего по рынку.

Сопроводительное письмо

I am writing to express my strong interest in the Machine Learning Engineer position at Cambridge Mobile Telematics. With over two years of experience in data science and a solid foundation in developing deep learning models, I am particularly drawn to CMT's mission of using AI-driven insights to improve road safety. My background in Python, Pandas, and PyTorch, combined with my experience in processing complex datasets, aligns perfectly with the requirements for the IC2 Foundation Models contributor role.

In my previous work, I have successfully prototyped and deployed ML solutions that required a deep understanding of time-series data and pattern recognition. I am excited about the opportunity to work on DriveWell Atlas and contribute to the development of multi-modal foundation models. I am confident that my technical skills in model optimization and my ability to collaborate across cross-functional teams will allow me to make a significant impact at CMT.

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Присоединяйтесь к CMT, чтобы создавать ML-модели нового поколения и делать дороги по всему миру безопаснее!

Описание вакансии

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is 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. Auto insurers, automakers, commercial 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.

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.

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 responsibilities

Base Salary Range

  • The base salary range for this position is: $123,000 to $153,700. This range is specifically for Cambridge, MA

Additional Perks:

  • Feel great working to improve road safety around the world!
  • Join one of our many employee resource groups including Black, AAPI, LGBTQIA+, Women, Book Club and Health & Wellness
  • Extensive wellness, education and employee assistance programs
  • CMT will do all that is possible to support our employees and create a positive and inclusive work environment for all!

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives.

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 joinour growing team.

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.

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Навыки

  • Python
  • Pandas
  • NumPy
  • Scikit-learn
  • SQL
  • TensorFlow
  • Keras
  • PyTorch
  • Hadoop
  • Spark
  • Kafka
  • Ray
  • CUDA

Возможные вопросы на собеседовании

Проверка опыта работы с основным типом данных компании.

Расскажите о вашем опыте работы с временными рядами и сенсорными данными. С какими специфическими проблемами вы сталкивались?

Оценка навыков оптимизации моделей для продакшена.

Какие методы оптимизации и сжатия моделей (квантование, прунинг) вы использовали на практике?

Проверка инженерной культуры и навыков разработки.

Опишите ваш процесс перехода от прототипа модели в Jupyter Notebook к масштабируемому решению в продакшене.

Оценка знаний в области глубокого обучения.

В чем заключаются основные сложности при обучении Foundation Models на мультимодальных данных (GPS, инерциальные датчики)?

Проверка навыков работы с Big Data.

Каков ваш опыт работы с распределенными системами обработки данных, такими как Spark или Ray?

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cambridgemobiletelematics
Страна
США
Зарплата
123 000 $ – 153 700 $