MLOps Engineer

About the role

As an MLOps Engineer at Eqvilent, you will focus on improving machine learning model pipelines, ensuring data quality, and building monitoring systems. Your work will involve designing ELT pipelines and automating the retraining and validation of models.

You will collaborate with a team of international professionals in a supportive environment that values innovation and continuous improvement. Success in this role means effectively implementing CI/CD pipelines and monitoring frameworks to ensure the reliability of ML models in production.

The salary range for this position is between $80,500 and $138,000, reflecting the competitive nature of the role.

Skills that matter here

• Python: This role requires strong knowledge of Python for developing and improving machine learning pipelines.
• Docker: Familiarity with Docker is essential for deploying models and ML services.
• MLOps: Experience in MLOps is needed to automate model retraining and validation.
• CI/CD: You will implement CI/CD pipelines for efficient deployment of ML services.
• PyTorch: Experience with PyTorch is a plus for working on machine learning models.
• Grafana: Knowledge of Grafana or similar monitoring frameworks will aid in monitoring ML models.

Who this role suits

• You have a solid technical background with experience in MLOps and machine learning.
• You thrive in collaborative environments and value support from your team.
• You are proactive in seeking challenges and opportunities for professional growth.
• You appreciate a flexible work environment that allows you to work remotely.

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