Position: Data Engineer or MLOps Engineer (Senior or Lead)
Company: Data Science UA
Experience required: 3y
Category: Data Science
English level: intermediate
Published: 2021-11-01T00:00:00+02:00

At Samba TV, we are on a mission to fundamentally change television viewing for everyone. We are doing this by leveraging our data to enable advertisers to engage and measure TV viewers across all their devices. We have an amazing story with a unique perspective formed by innovative technology.

SambaTV’s Core AI team is in charge of building models for the next generation of AI-powered TV products. We are responsible for the end-to-end development of our models, including:
- dataset collection using geographically-distributed television labs;
- model training in the cloud using serverless GPU clusters;
- model optimization for constrained computation on the edge;
- model testing using both virtual and real televisions; and
- creation of the data pipelines and tooling that makes the above possible.

As a member of our team you will be working at the intersection of engineering, science, and entertainment. As a Data Engineer/MLOps Engineer, you make it all possible. You enable the team by building robust data pipelines and tooling for accelerating the Model Development Life Cycle.

Responsibilities:
- Design, build, and maintain ML data pipelines (for training/test video from television labs, model artifacts, model evaluation results and summaries, etc.) that are scalable, robust, and secure
- Promote great software engineering practices and help improve our processes and establish new ones
- Enable Machine Learning engineers to succeed in the end-to-end model development process by designing tools and processes that simplify working with labelled data, features, models, and relevant metrics

Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related field
- 4+ years of professional development experience building high-performance, large-scale applications/pipelines with solid experience in Python
- Solid foundation in computer science, with strong competencies in data structures, algorithms and software design
- Demonstrated self-motivation and willingness to dive into complicated DevOps challenges with a strong command of Linux and version control systems
- Experience with at least one distributed computation framework (Spark, Hive, Dask, Metaflow, etc.) and at least one job orchestration framework (Airflow, Luigi, etc.)
- Strong verbal and written communication skills

Preferred Qualifications
- Experience with components of modern Machine Learning architectures—feature stores, model stores, evaluation stores, etc.
- Familiarity with cloud providers and serverless architectures (Amazon Web Services, Google Cloud, etc.)
- Familiarity with container orchestration tools (Kubernetes, ECS, etc.) in a production setting
- Experience working with video—video capture, video processing, transcoding, frame analysis, ffmpeg