MLOps Engineer

2 weeks ago

Gurugram, India Pylon Management Consulting Full time

Responsibilities : - Develop, optimize, and maintain scalable machine learning pipelines for training, evaluation, and deployment.- Work with research and product teams to productionize AI/ML models, ensuring reliability, scalability, and performance.- Automate workflows for data preprocessing, model training, validation, and monitoring.- Implement robust monitoring systems for detecting data drift, model degradation, and system anomalies.- Build APIs, services, and tools that integrate models seamlessly into end-user applications.- Ensure reproducibility, experiment tracking, and version control using modern MLOps practices.- Collaborate with engineers to optimize inference performance and reduce latency in production.- Stay updated on best practices in applied ML, data engineering, and MLOps.Requirements : - Experience in building and deploying ML models into production.- Strong proficiency in Python and ML frameworks (e. g., PyTorch, TensorFlow, Scikit-learn).- Experience with data processing frameworks (e. g., Pandas, Spark) and scalable data pipelines.- Hands-on experience with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).- Familiarity with CI/CD pipelines and workflow orchestration tools (Airflow, Prefect, Dagster).- Strong understanding of software engineering principles, APIs, and system design.- Ability to debug, optimize, and scale ML workloads in production environments.Bonus Points : - Experience with monitoring/observability tools for ML systems (e. g., Evidently AI, Prometheus, Grafana).- Exposure to vector databases, RAG pipelines, or real-time inference systems.- Familiarity with MLflow, Kubeflow, or other experiment management platforms.- Contributions to open-source ML/MLOps projects. (ref:hirist.tech)

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