ML Ops Engineer – Senior Associate

[{"text":"00N0I00000KT1fD","value":"utm_source"},{"text":"00N0I00000KT1fI","value":"utm_medium"},{"text":"00N0I00000KT1fN","value":"utm_campaign"},{"text":"00N0I00000KT1fS","value":"uterm"},{"text":"00N0I00000KT1md","value":"adgroupname"},{"text":"00N0I00000KT1mx","value":"keyword"},{"text":"00N0I00000KT1nR","value":"creative"},{"text":"00N0I00000KT1ng","value":"devicemodel"},{"text":"00N0I00000KT1nq","value":"placement"},{"text":"00N0I00000KT1ot","value":"target"},{"text":"00N0I00000KT1o0","value":"device"},{"text":"00N0I00000KT1o5","value":"network"},{"text":"00N0I00000KT1oA","value":"matchtype"},{"text":"00N0I00000KT1oF","value":"gclid"},{"text":"00N0I00000KT1nM","value":"campaignname"},{"text":"00N0I00000KT1n7","value":"term"},{"text":"00N0I00000KT1fS","value":"utm_term"},{"text":"00N0I00000KQo5v","value":"utm_content"},{"text":"","value":""}]

ML Ops Engineer – Senior Associate ( Executive Education )

Job Title:	ML Ops Engineer – Senior Associate	Function:	Analytics
New / Replacement role	New	Department:	EE
Reports to position:	Associate Director	Location:	Hyderabad
Reportees to Position:	None	Band:	A4

Job Purpose

Data Preparation for Analysis & Modelling - Data Extraction, Cleaning, Joining & Transformation
Generating Reports based on requirements
Building Data Processing Pipelines for Modelling from different sources
Deploying ML Models in Production and integration with other Systems
Monitoring and Maintenance of Data flow in Models deployed in Production

Job Outline

Collaborate with Business and IT teams for understanding and collecting data.
Assist the Analytics Head in Data Preparation for Analysis & Modelling - Data Cleaning, Joining & Transformation.
Generate Ad-Hoc reports on demand in Python/Excel.
Build automated data pipelines for analysis and modelling in the Python coding environment. Implementing pipelines for automated testing, building, and deploying machine learning models built in Python. Build Data Pipelines from different sources like

1. SQL Server

2. SalesForce – Tabular, Text and Call Logs

3. Learning Management Systems

4. Web-Scraping

5. Adobe Email Marketing Cloud

6. Call Log Audio data from Systems like OzoneTel

7. Excel, emails etc

8. Other systems as and when required…

Deploy ML Models (built in Python) in production and ensure model outcome flows back seamlessly into platforms like SalesForce.
Run and maintain the models in Production
Monitoring and Maintenance of Data flow in Models deployed in Production

Job Specification
Knowledge / Education	Skills	Work Experience
BE/ B.Tech – Any Stream	Proficient in Python, Spark (PySpark), and SQL, scikit-learn and/or any other platforms required for above Job Outline.	3-5 years of experience in building data pipelines and Model deployments. Proficient in setting up version control systems like Git or Jupyter Notebooks for tracking changes in code and model versions. Hands-on experience with deploying popular machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn etc. Experience with containerization tools like Docker and container orchestration systems like Kubernetes. Experience deploying ML services and applications to at least one major cloud platform (AWS, Azure, GCP etc)

Job Interface/Relationships:
Internal	External
Work with All vertical/function teams within EE and DL Work extensively with the DT(IT) team

S.No	Key Responsibilities	% Time Spent
1	Build Data Pipelines for predictive models and deployment from different sources	30%
2	Deploying ML Models in Production and integration with other Systems	30%
3	Monitoring and Maintenance of Data flow in Models deployed in Production	10%
4	Data Preparation for Modelling - Data Cleaning, Joining & Transformation. Generate Ad-Hoc Reports on demand.	30%
	Total Time Spent on All Responsibilities	100%