Machine learning ops engineer

Job Description

Why Lytx? :

As our Cloud Operations Engineer - Machine Learning you will join our Applied Machine Learning Team who develops machine learning and computer vision algorithms to monitor and assess the state of drivers and their environments to identify risk and improve safety for our clients. You will contribute to all aspects of the development cycle to optimize workflows, dataset generation, model performance and code efficiency to help enhance and differentiate us as the leader in the Video Safety and Telematics industry. If this sounds like you, we encourage you to apply!

What You'll Do :

Build and maintain cloud deployment of ML models and surrounding infrastructure

Contribute to infrastructure and process improvements for data collection, labeling, model development and deployment

Design and implement R&D data engineering solutions for delivery of ML model value from device to cloud, including message payload design, data ingest and database architecture

Help prepare and automate builds for device model deployment

Assist on projects led by other team members via data processing, programming, monitoring of production applications, etc.

Other duties as assigned.

What You'll Need :

Bachelor’s degree in Computer Science or equivalent experience

1 to 4 years of experience with a Strong background in MLOps, Python, GNU / Linux CLI

Versatile and adaptable engineer who can address evolving needs of team.

Strong understanding of data engineering principles and architecture

Knowledge of relational database modeling and integration. Experience with No SQL is helpful.

Ability to manage cloud resources and technologies within AWS, including Sagemaker, EC2 and S3

Experience with software automation tools, e.g., Airflow, Ansible, Terraform, Jenkins

Experience with automated unit testing and regression testing methodologies

Familiar with Linux software build toolchains and patterns. (e.g., Make, gcc)

Experience with source control and tracking (git)

Strong teammate who enjoys working in a collaborative, fast-paced team-focused environment