<p><p><b>Job Title :</b> MLOps Engineer<br/><br/><b>Location :</b> Bangalore / Gurgaon<br/><br/><b>Experience :</b> 4 to 8 years<br/><br/><b>Employment Type :</b> Full-time<br/><br/><b>Notice Period :</b> 15 days<br/><br/><b>About the Role :</b><br/><br/>We are seeking an experienced MLOps Engineer who can bridge the gap between Machine Learning and DevOps.</p><p><br/></p><p> You will be responsible for designing, building, and maintaining scalable pipelines to deploy, monitor, and manage machine learning models in production environments.
</p><p><br/></p><p>This role requires strong programming skills, expertise in MLOps tools, and hands-on experience with cloud platforms.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Design, implement, and manage CI/CD pipelines for ML model training, deployment, and monitoring.<br/><br/>- Automate data preprocessing, model training, testing, and production deployment workflows.<br/><br/>- Set up model monitoring, logging, and alerting to ensure performance and reliability.<br/><br/>- Collaborate with data scientists and software engineers to integrate models into production systems.<br/><br/>- Optimize infrastructure for scalability, cost-effectiveness, and high availability.<br/><br/>- Ensure compliance with security, governance, and best practices in ML lifecycle management.<br/><br/><b>Primary Skills & Qualifications :</b><br/><br/>- Strong programming skills in Python with a focus on ML/AI workflows.<br/><br/>- Hands-on experience with Docker and Kubernetes for containerization and orchestration.<br/><br/>- Proficiency in MLOps tools such as Kubeflow, MLflow, or similar frameworks.<br/><br/>- Experience with cloud platforms like AWS SageMaker, Azure ML, or equivalent.<br/><br/>- Knowledge of CI/CD tools (e.g., Jenkins, GitLab CI, GitHub Actions) and version control systems (Git).<br/><br/>- Familiarity with model monitoring, model registry, and reproducibility best practices.<br/><br/><b>Good to Have :</b><br/><br/>- Experience with Terraform or other Infrastructure-as-Code (IaC) tools.<br/><br/>- Exposure to big data frameworks like Spark or Kafka.<br/><br/>- Understanding of data engineering pipelines and ETL processes.<br/><br/><b>Why Join Us : </b><br/><br/>- Opportunity to work on cutting-edge ML infrastructure at scale.<br/><br/>- Collaborative and innovative environment.<br/><br/>- Competitive compensation and growth opportunities.</p><br/></p> (ref:hirist.tech)