Remote AI/MLOps Engineer

Summary

The job is for an AI/MLOps Engineer at Apolo, a company that simplifies AI/ML operations. The role involves managing product deliverables with technical expertise and proactively researching new technologies. Ideal candidates have knowledge of ML-driven projects lifecycle, Kubernetes, Containerd / Docker, Helm, CI/CD practices, GitHub Actions, MLOps best practices, and Python. Desirable skills include networking and experience with specific tools.

Requirements

• Understanding of ML-driven projects lifecycle
• Knowledge and hands-on experience with Kubernetes, Containerd / Docker, Helm, CI/CD practices, particularly with GitHub Actions
• Basic understanding of MLOps best practices (data and model versioning, experiment tracking, reproducibility, etc.)
• Proficient in Python for scripting, automation, and integration

Responsibilities

• Build complex automated reproducible pipelines for the entire ML project lifecycle, including data management, experimentation, model training, deployment, and monitoring in production
• Build reusable integrations and applications for each stage of the ML project lifecycle
• Monitor the MLOps tools/approaches landscape to actively identify solutions for various domain problems
• Participate in the development of MLOps platform services
• Communicate with end users to understand their pain points
• On-board end users to the MLOps platform

Preferred Qualifications

• Networking including TCP/IP, DNS, load balancing, and requests routing to ensure secure and efficient network operations
• Experience with Pachyderm, DVC, KubeFlow, Spark, MLFlow, Seldon or their alternatives
• Experience with LLM deployment at scale

Benefits

• Work remotely, ensuring time zones align for effective collaboration
• Shape the product's direction and success by taking ownership of essential components
• Solve complex and innovative challenges
• Join a supportive and dynamic team environment
• Receive a competitive salary and benefits package
• Effective collaboration is ensured by aligning time zones for remote work