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Senior Machine Learning/AI Operations Engineer

AMODO

AMODO

Software Engineering, Operations, Data Science
Cambridge, MA, USA
Posted on Wednesday, November 15, 2023

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®, 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. Companies from personal and commercial auto insurance, automotive, rideshare, smart cities, wireless, financial services, and family safety industries use insights from CMT’s platform to power their risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT serves millions of people through over 95 programs in 25 countries, including 21 of the top 25 US auto insurers.

We are in search of an organized, team-oriented self-starter to support our Data Science team by optimizing our utilization of Databricks, Spark, Ray, and AWS services for building large-scale machine learning models. As a Senior Machine Learning/AI Operations Engineer, you will play a crucial role in developing and managing the infrastructure supporting the testing and deployment of machine learning models for product releases. This position involves collaborating closely with data scientists, mobile developers, platform engineers, and QA engineers to foster a collaborative and innovative environment.


The ideal candidate for the Senior Machine Learning/AI Operations Engineer role is an accomplished expert, bringing significant expertise in optimizing and deploying large-scale machine learning models. They possess a track record of success in architecting scalable ML infrastructure and excel in collaborative, fast-paced environments, ensuring the seamless deployment and monitoring of advanced AI technologies.

Responsibilities:

  • Develop and optimize scalable machine learning infrastructure, ensuring a balance between cost-efficiency and speed; with the goal of empowering the data science team
  • Build robust infrastructure to expedite the delivery of new models, enhancing the efficiency of feature engineering, model training, and validation processes
  • Offer expert insights on current research trends, enabling the implementation of scalable and cost-effective solutions
  • Establish a monitoring infrastructure for evaluating the performance of machine learning models at scale, including those deployed on mobile devices
  • Stay abreast of the latest advancements in training, deployment, and mobile applications of machine learning technologies
  • Architect software solutions seamlessly integrating mobile, backend, and research domains, facilitating effective data collection and transmission to support our models
  • Develop comprehensive test plans, ensuring smooth deployment of new models across backend and mobile platforms
  • Complete any additional tasks as they arise

Qualifications:

  • Bachelor’s degree or equivalent years of experience and/or certification
  • 4+ years of relevant working experience, with experience working as a Data or ML Engineer a plus
  • Expertise in Big Data infrastructure and software (e.g. Databricks, SageMaker, Spark, S3)
  • Expertise of software development process, and ability to code in scripting languages for data manipulation (e.g. Python, Pandas, NumPy, scikit-learn, SQL)
  • Hands-on Kubernetes framework experience in management, configuration, deployment, and troubleshooting
  • Design and document systems, including writing and reviewing code, to automate away problems within the squad’s domain
  • Proficiency in at least two programming languages, with Python being a must - we work primarily in Python with smatterings of shell scripting
  • Good understanding of AWS services
  • Demonstrated experience with Linux

Nice to Have:

  • Experience using EC2, Lambda, Dynamo, RDS (PostgreS), S3, Kinesis
  • Experience with Docker, NGinX, PostgreSQL, Terraform
  • Experience building scalable data processing systems for production environment
  • Experience with deep learning frameworks e.g. TensorFlow, Keras, Torch, visualization and performance
  • Ability to navigate code, request data from data sources and code for bug fixes
  • Actively seeks feedback and resolve discrepancies with senior team members
  • AWS Certification and/or Kubernetes Certification

Compensation and Benefits:

  • Fair and competitive salary based on skills and experience
  • Equity 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

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 are intensifying our commitment to provide opportunities and career growth to the underrepresented. We are focused on creating an inclusive work environment that encourages a diversity of background and thought to produce the best products and services within our industry.

CMT is an equal opportunity employer and strives to create an inclusive and diverse environment that enriches our employees’ lives in and outside of work. We do not discriminate on the basis of 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 Twitter @cmtelematics.