Ml Ops

12 hours ago

Mumbai Maharashtra, India Clowise Business Solutions Full time

Location: Mumbai City (Work from office only)

Key Responsibilities
- Manage end-to-end deployment of ML models on both on-premise servers and AWS
- Build and manage Big Data infrastructure and pipelines for high-volume data processing
- Develop and maintain CI/CD pipelines for ML models.
- Deploy, monitor and optimize machine learning models in AWS environments.
- Automate model training, validation and retraining workflows.
- Implement data versioning, model versioning, and lineage tracking using tools like DVC, MLflow, or SageMaker.
- Ensure model performance monitoring, logging, and alerting using Prometheus, Grafana, or ELK stack.
- Work with Docker & Kubernetes for containerized deployments.
- Optimize ML model inference pipelines for low latency and cost efficiency.
- Collaborate with Data Engineers to streamline data pipelines for ML workloads.
- Ensure security, compliance, and governance for deployed models.
- Write efficient Python scripts for automating MLOps tasks.
- Perform basic SQL queries for data validation and monitoring.
- Support hyper parameter tuning and model optimization strategies.

**Required Skills**:

- Bachelor’s/Master’s degree in Computer Science, Data Science, or a related field.
- 2+ years of hands-on experience in MLOps, LLM Ops or related fields.
- Experience with AWS (S3, Lambda, SageMaker, EKS, Step Functions, Glue, CloudWatch, IAM).
- Hands on Experience in MLflow, Kubeflow, SageMaker, Airflow
- Hands on experience with tolls like Hadoop, Kafka or Spark
- Strong Python programming skills, with experience in TensorFlow, PyTorch or Scikit
- learn.
- Proficiency in Docker, Kubernetes, CloudFormation or Terraform.
- Experience with CI/CD tools like GitHub Actions, Jenkins, GitLab CI/CD.
- Good understanding for Big Data Frameworks
- Familiarity with model monitoring and drift detection frameworks.
- Strong debugging and problem-solving skills for production ML models.
- Knowledge of Databricks, Airflow, Kafka, or Spark.
- Exposure to LLMs (Large Language Models) and Generative AI deployments.
- Knowledge of cost optimization strategies for cloud-based ML workloads.

Pay: ₹1,200,000.00 - ₹2,000,000.00 per year

Ability to commute/relocate:

- Mumbai, Maharashtra: Reliably commute or planning to relocate before starting work (required)

Application Question(s):

- Post selection, can you join immediately or within 30 days?

**Experience**:

- ML Ops / LL Ops: 2 years (required)

Work Location: In person

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