Location: Remote
About Us:
At Apolo, we're committed to simplifying AI/ML operations for organizations. By addressing the deployment challenges of AI/ML in varied environments, we provide cost-effective and hassle-free solutions. Our managed services and comprehensive tools allow businesses to focus on their core objectives, ensuring seamless AI adoption and innovation without the operational complexity.
The Role:
We are looking for a senior AI/MLOps Engineer who will be crucial in managing and evolving our product deliverables. This role requires technical expertise, and a proactive mindset eager to research and try new technologies. Ideal candidates are resourceful, excel in problem-solving, and capable of working autonomously with minimal supervision.
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
Qualifications:
- 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
The final screening will involve a test assignment. Please make sure you are comfortable completing it post interview. Make sure you feel you will do well.
Desirable Skills:
- Networking including TCP/IP, DNS, load balancing and requests routing to ensure secure and efficient network operations
- Experience with MLOps tools like: Pachyderm, DVC, KubeFlow, Spark, MLFlow, Seldon or their alternatives
- Experience with LLM deployment at scale
What We Offer:
- 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.
