Associate Vice President

1 month ago

Gurugram, India HuQuo Full time

Job Description :


- Data Pipeline Deployment : Collaborate with data engineers and data scientists to deploy data pipelines and machine learning models into production environments.

- Model Versioning : Implement version control for machine learning models to ensure reproducibility and traceability.

- Continuous Integration/Continuous Deployment (CI/CD) : Implement and manage CI/CD pipelines for data and ML deployment and setup configuration based automated CI/CD pipelines

- Orchestration : Integration data pipelines/products with orchestration tools like Airflow

- Monitoring and Alerting : Implement & automate monitoring and alerting systems to proactively detect and address issues in data pipelines, machine learning models and infra

- Automation : Develop automation scripts and tools for managing data and ML operations, including data ingestion, feature engineering, model training, and deployment.

- Scalability : Ensure that data and ML pipelines can scale with the growing volume of data and usage demands.

- Performance Optimization : Identify and address performance bottlenecks in data and ML pipelines.

- Security : Implement security best practices to protect sensitive data and machine learning models.

- Collaboration : Collaborate with data engineers, data scientists, and IT teams to resolve technical issues and optimize data and ML workflows.

- Documentation : Maintain detailed documentation for data and ML operations processes, configurations, and updates.

- Work with multiple clients, identify ops opportunities in the form of gaps or new scope, work on solution design for the same.

- Setting up Ops frameworks, processes & teams from scratch

- Research on new tools, tech & trends in the market, create PoVs on where they fit in the Operations scope and how they support the client architectures.

- Business Development in the form of RFP responses, building accelerators, ops products etc

Preferred Qualifications :

- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

- Proven experience in data & machine learning operations, or a related role.

- Must have lead Operations & support team in the past

- Awareness of L1 to L4 Ops support model, responsibilities & activities involved in each level

- Good knowledge of data engineering tools and frameworks (e.g., Apache Spark, Kafka, Airflow, Hadoop, Hive, Greenplum).

- Scripting and programming skills in languages such as Python, SQL

- Strong experience in Unix

- Proven experience in E2E process automation in automating monitoring, alerting & DQ frameworks

- Proficiency in CI/CD tools like Git, Jenkins, Concourse, Ansible, Chef, Puppet etc. Git, Jenkins must, any one from rest of them

- Hands-on experience in monitoring & alerting tools like Prometheus, Grafana, Datadog, Nagios, Datadog, Montecarlo, New Relic, Dynatrace etc any one or two

- Working knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes) and integrating it with the CI/CD pipeline

- Working knowledge of integrating Unit & Integration test cases with the CI/CD pipelines

- Understanding of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

- Hands-on experience in MLOps tools like MLFlow, Torchserve, Kubeflow, Vertex AI, Sagemaker, etc

- Experience of at least one cloud platforms (e.g., AWS, Azure, GCP) along with related Ops tools like Cloudwatch, Cloud Monitoring, Cloud Deploy, CodePipeline, Azure Devops etc.

- Working knowledge of Cloud Infra automation tools like Terraform, Cloud Formation, Resource Manager, etc

- Excellent problem-solving and troubleshooting skills.

- Strong communication and collaboration skills.

(ref:hirist.tech)

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