Natobotics - MLOps Lead - Data Modeling

5 days ago

Mumbai, India Natobotics Technologies Pvt Limited Full time

Job Title : MLOps Lead

Location : Hyderabad / Bengaluru / Chennai / Pune / Mumbai / Noida

Experience Required : 7 to 12 Years

Notice Period : Immediate to 30 Days

Interview Mode : Virtual

Employment Type : Full-time

Client : Leading MNC

Position Overview :


We are looking for a highly skilled MLOps Lead to drive the deployment, automation, and scalability of Machine Learning models in production environments. The ideal candidate will have deep expertise in MLOps tools and frameworks such as MLflow and Kubeflow, strong programming skills in Python, and hands-on experience with DevOps practices, CI/CD pipelines, and AWS cloud infrastructure. This role requires both leadership and technical proficiency to guide teams in delivering secure, reliable, and high-performing ML solutions at scale.

Key Responsibilities & Model Deployment :


- Design, implement, and maintain MLOps pipelines for model training, validation, deployment, and monitoring.


- Utilize MLflow, Kubeflow, or similar platforms for experiment tracking, model registry, and serving.


- Automate ML workflows, including data ingestion, feature engineering, and model & DevOps :


- Build and maintain CI/CD pipelines for ML applications using tools like Jenkins, GitLab CI, or AWS CodePipeline.

- Deploy scalable ML infrastructure on AWS using services like S3, Lambda, SageMaker, EKS, EC2, and CloudFormation/Terraform.

- Integrate containerization technologies (Docker, Kubernetes) for reproducible and scalable deployments.

Monitoring & Optimization :


- Implement monitoring for model performance, data drift, and resource utilization.

- Establish feedback loops for continuous improvement of models in production.

- Ensure cost-effective cloud resource usage without compromising performance.

Collaboration & Leadership :


- Work closely with data scientists, data engineers, and product teams to operationalize ML solutions.


- Mentor junior engineers and establish MLOps best practices across teams.

- Participate in architectural discussions and technical decision-making for ML systems.

Required Skills & Qualifications :


- 7 - 12 years of overall IT experience with at least 4+ years in MLOps/ML Engineering.


- Hands-on expertise with MLflow and Kubeflow for model management and deployment.

- Strong programming skills in Python (Pandas, NumPy, Scikit-learn, etc.).

- Solid experience with DevOps practices and building CI/CD pipelines.

- Proficiency in AWS cloud services related to ML (SageMaker, EKS, S3, EC2, Lambda, etc.).

- Experience with Docker and Kubernetes for container orchestration.

- Knowledge of Git or other version control systems.

Preferred Skills :


- Exposure to GCP or Azure MLOps toolchains.


- Familiarity with monitoring tools like Prometheus, Grafana, or ELK Stack.

- Knowledge of data versioning tools like DVC.

- Understanding of data security, compliance, and governance in ML pipelines.


(ref:hirist.tech)

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