MLOps Engineer

About the role

This role focuses on enhancing the machine learning lifecycle by designing and building pipelines for data processing and analysis. The engineer will construct MLOps pipelines to automate model retraining and validation, ensuring models are continuously improved and maintained. A key aspect of the work involves implementing CI/CD pipelines for deploying models and ML services into production environments.

The MLOps Engineer will also be responsible for creating and maintaining systems to monitor ML models once they are in production. This includes ensuring data quality, testing model correctness, and building robust monitoring frameworks. The goal is to ensure the reliability and performance of machine learning solutions.

Success in this position means contributing to a streamlined and efficient machine learning operation. This involves working with a team of international professionals to tackle challenges related to ML model deployment and monitoring. The role emphasizes a commitment to fostering a supportive environment while utilizing cutting-edge technology.

The salary for this role ranges from $80,500 to $138,000 annually.

Skills that matter here

• Python: This role requires strong knowledge of Python for designing and building ML pipelines and services.
• Docker: Familiarity with Docker is necessary for containerizing ML applications and services.
• MLOps: The position involves constructing MLOps pipelines for automated model retraining, validation, and monitoring.
• CI/CD: Experience with CI/CD is needed for implementing deployment pipelines for ML models and services.
• PyTorch: Experience with PyTorch is a plus, indicating work with specific machine learning frameworks.
• Grafana: Experience with Grafana or similar monitoring frameworks is beneficial for creating ML model monitoring systems.

Who this role suits

• A person who thrives on improving and automating machine learning workflows.
• Someone with a background in ensuring the quality and correctness of data and models.
• An individual who values working in a supportive, international team environment.
• A candidate who is comfortable with remote work and managing their own schedule.

From the employer

WHAT YOU’LL BE DOING:

• Design and build ELT pipelines for data processing and analysis.
• Construct MLOps pipelines for automated retraining and validation of models.
• Implement CI/CD pipelines for deploying models and ML services.
• Create services for monitoring ML models in production.

WHAT WE LOOK FOR IN YOU:

• Strong knowledge of Python
• Familiarity with Docker
• Basic understanding of machine learning concepts and techniques

WHAT WILL BE A PLUS:

• Experience with PyTorch
• Knowledge of Dagster
• Experience automating ML pipelines from data ingestion to deployment with monitoring and observability
• Experience with monitoring frameworks (Grafana, Prometheus, or similar)
• Understanding of distributed training systems for ML models

WHY SHOULD YOU JOIN OUR TEAM?

• Great challenges with many opportunities to prove yourself
• A welcoming group of highly qualified international professionals
• Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment
• Cutting-edge hardware and technology
• Work remotely from anywhere in the world
• Access any of our global offices anytime
• 40 paid days off
• Competitive salary