MLOps Engineer

Prior experience with a focus on deploying and managing machine learning models, data engineering, working knowledge of DevOps and Software Engineering is preferred

Proven ability in Python programming and exposure to Python's ML ecosystem.

Experience with AWS cloud based machine-learning deployments & tools (e.g. SageMaker, Event Bridge, ECS, ALB).

Experience with DBT

Experience deploying infrastructure as code.

Extensive experience with cloud and distributed systems, data-intensive applications, and large-scale system design.

Experience with AI solutions (e.g. Agents use and deployment)

Experience with data warehouse (BigQuery, SnowFlake)

Familiarity with Large Language Models

Understanding containerization technologies (e.g. Docker).

Knowledge of software development practices, version control, and collaboration tools (e.g., Git, GitHub & actions)

Understanding standard ETL patterns, modern data warehousing and data quality practices regarding test driven design and data observability.

Exceptional stakeholder management and communication skills to effectively communicate across global teams

Experience implementing real time data systems [an advantage]

Experience with Streamlit [an advantage]

WHATS IN IT FOR YOU?

The opportunity to work with a fantastic team with a great culture

• The opportunity to be part of an innovative and exciting company that is completely changing an outdated industry

• The opportunity to grow professionally in a dynamic and fun environment • A competitive compensation plan

• Hybrid work from home and office model

• A flexible time off policy which includes unlimited wellness days, personal days and vacation time

• Two volunteer days

• A day off on your Birthday

The company paid top-tier health benefits plan and a telemedicine service