MLOps Engineer Jobs in Coimbatore AI and ML Company

📋 Job Description

Jobzi is sourcing qualified candidates for MLOps Engineer positions in Coimbatore's private AI and ML Company sector. This is a full-time opportunity with a reputed Artificial Intelligence and Machine Learning employer in Coimbatore offering competitive salary, structured growth, and a professional work environment. Tamil communication skills are preferred alongside English for professional and business interaction in Coimbatore.

📌 Key Responsibilities

• Design and maintain ML pipelines for training, evaluation, and deployment using Kubeflow or Airflow
• Implement CI/CD workflows for ML model code, data, and experiment versioning
• Set up and manage model serving infrastructure using Triton, TorchServe, or FastAPI-based endpoints
• Monitor deployed models for data drift, prediction distribution shift, and performance degradation
• Manage experiment tracking, model registry, and lineage using MLflow or equivalent platforms
• Collaborate with ML engineers and data engineers to improve pipeline reliability and scalability
• Automate retraining triggers based on performance thresholds and data freshness criteria

🎓 Qualifications and Requirements

• B.E. in Computer Science with 2 to 6 years of MLOps or ML platform engineering experience
• Hands-on experience with MLflow for experiment tracking and model registry management
• Proficiency in Docker and Kubernetes for containerised ML workload deployment
• Experience building CI/CD pipelines for ML using tools such as GitHub Actions, Jenkins, or GitLab CI
• Knowledge of model serving platforms and inference optimisation fundamentals
• Familiarity with data quality monitoring and drift detection tools
• Strong scripting skills in Python and Bash for pipeline automation
• Good Tamil and English communication skills for team coordination and client interaction in Coimbatore.

✅ Required Skills

🏆 Certifications and Qualifications

M.Sc./Ph.D. in Computer Science, Mathematics, or Statistics for research roles; B.E. CS with deep learning frameworks (TensorFlow, PyTorch) for ML engineer roles; AWS Machine Learning Specialty or cloud provider Professional Machine Learning Engineer certifications for cloud ML roles; Coursera Deep Learning Specialization (Andrew Ng) widely recognised; Hugging Face certifications for LLM roles; Databricks ML Professional for MLOps roles; NVIDIA Deep Learning Institute certifications for GPU computing and inference optimisation roles