MLOps Engineer

Zest for Tech is a Series B backed startup focused on scaling their proven product in the market. They are seeking a Senior MLOps Engineer to build and scale infrastructure for ML models, manage end-to-end ML pipelines, and collaborate with teams to enhance ML applications.

Responsibilities:

• Build and scale infrastructure for training, deploying, and serving ML models in production
• Develop and manage end to end ML pipelines across data, training, evaluation, and deployment
• Implement CI/CD workflows to streamline model experimentation and releases
• Introduce and own experiment tracking, model versioning, and ML lifecycle best practices
• Establish monitoring, logging, and observability for model performance and data quality
• Collaborate closely with ML and NLP teams to productionise LLM and agentic applications
• Improve system efficiency and delivery velocity across the ML platform

Requirements:

• Strong Python engineering skills and experience with modern MLOps tooling
• Hands on experience with cloud infrastructure (AWS preferred) and scalable ML deployments
• Deep familiarity with Docker, Kubernetes, and model serving architectures
• Experience building orchestration pipelines (Airflow, Prefect, Ray, or similar)
• Proven track record taking ML models from experimentation to reliable production systems
• Experience with experiment tracking tools (e.g. MLflow, Weights & Biases) and lifecycle management
• Bonus: experience supporting LLM, RAG, or NLP pipelines in production environments