Job Location: Hyderabad/Secunderabad
Roles and Responsibilities
At least 4+ years experience working as MLOps/Data Engineer.
1. At least 2+ years of proven Python programming experience (experience in most of common libraries like numpy, pandas, mathplotlib, etc)
2. Hands-on experience with scripting and coding using Python, Linux Shell
– Understanding of tools for ETL, databases, data engineering
3. Must have worked as MLOps data engineer in at least 2+ projects
– Must have understanding of ML Development Lifecycle (concepts)
– Must have understanding of end-to-end ML Ops Lifecycle, using relevant tools/platforms
– Must have implemented model serving patterns/pipelines
– Should have understanding of Model Monitoring & Model Management
4. Good, hands-on experience with Linux & Containerized environments:
– Experience with Kubernetes or Docker Swarm; at least 2 projects.
– Experience with scheduling tools like Airflow, Luigi,etc. (using MLFlow/Kubeflow/ClearML);
5. Understanding of automation builds (such as Jenkins/CloudBees)
– Familiarity with standard concepts and technologies used in CI/CD build, deployment pipelines, along with standard software development and release management practices
– Experience with configuration using tools such as Chef, Ansible
– Experience with APIs/JSON
6. Understanding of big data technologies (Hadoop/HDFC, Hive, Spark, Kafka, Zookeeper) and must have worked with large datasets, implemented data pipelines ( 2 projects)
– Data ingestion, validation, storage, security
– Data processing / mining
Desired Candidate Profile
Perks and Benefits
You will contribute to the role by:
- Driving customer success: Delivering successful implementation or management of MLOps/Data Science initiatives and projects
- Showing technical excellence: Establish and perform at high technical competency, to create customer and business impact
- Value creation: Build and progress on a strong career growth path
- Innovating continuously: Solving problems with effective, innovative solutions enabling cross-functional teams to serve business
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