Machine Learning Operations Lead
1 month ago
ResourceTree Global Services is hiring ML Ops Lead for its Leading Data Analytics Client. Below are the details
Job Title : Machine Learning Operations Lead (ML Ops Lead)
Experience : 8 Years
Location : Hyderabad (Hybrid), Bangalore (Hybrid)
Key Responsibilities :
- Design and implement MLOps pipelines using tools and frameworks like TensorFlow Serving, Kubeflow, MLflow, or similar solutions.
- Design, develop, and implement data pipelines and engineering infrastructure to support enterprise-scale machine learning systems. This could involve tasks such as data ingestion, pre-processing, transformation, feature engineering, and model training.
- Design and implement cloud-based MLOps solutions using platforms like Azure ML, Azure Databricks, AWS SageMaker, or Google Cloud AI Platform
- Hands-on experience with Azure cloud services, including Azure ML, Azure DevOps, AKS, Azure Container Registry (ACR), Azure Application Insights, and Azure Log Analytics, is essential.
- Experience in containerization technologies like Docker and Kubernetes is a plus.
- Experience deploying and maintaining various types of machine learning models in production, including text/NLP models, is required.
- Experience with Generative AI (GenAI) projects is a plus.
- Build CI/CD pipelines using tools like GitLab CI, GitHub Actions, Airflow, or similar solutions to automate the ML lifecycle.
- Perform data science model reviews, including code refactoring and optimization, containerization, deployment, versioning, and monitoring of the model's quality.
- Support data model development, with a focus on auditability, versioning, and data security. This could involve implementing practices like lineage tracking, model explainability, and bias detection.
- Mentoring junior MLOps engineers or collaborating with multiple teams like consulting, data engineering, development team.
- Total 7+ years of work experience , 3+ years in MLOps
- Strong expertise in GenAI, advanced NLP, computer vision, and ML techniques.
- Experience in designing, developing, and deploying production-grade AI solutions.
- Excellent communication and collaboration skills. Ability to work independently and as part of a team.
- Strong problem-solving and analytical skills.
- Stay up-to-date on the latest advancements in MLOps technologies and identify and evaluate new tools and techniques to improve the performance, maintainability, and reliability of machine learning systems.
(ref:hirist.tech)
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