Machine Learning Engineer - Data Modeling (4-8 yrs)

Title : Machine Learning Engineer

Experience : 4 - 6yrs Years

Work Location : Bangalore

Notice Period : Immediate to 30 Days Max only

Job Summary :

Minimum qualifications :

- 4years of experience with software development and testing in Python including object-oriented software engineering and building custom Python packages/libraries

- Experience using containers, designing, setting-up and managing git repos, CI/CD, and synchronized ml artifact versioning

- 4 years of experience with NLP and/or machine learning

- Excellent English communication skills and experience working on teams.

Preferred qualifications :

- 2 years of experience working with data engineering and data governance teams

- 2 years managing teams doing data work (data science, data engineering, ml engineering, ml ops, etc.)

- Experience architecting and setting-up cloud-native infrastructure for machine learning and NLP.

Client's NLP R&D group specializes in customized NLP and machine learning services for use cases across the company. We seek a talented and tenured engineer who will spearhead the development and implementation of ML Ops at Voya.

As a senior ML engineer, you will :

- Work with cross-functional teams across Voya to help guide the design and implementation of necessary ML Ops infrastructure in Azure Cloud and Databricks.

- Collaborate with and mentor software and data engineers on the team.

- Establish and improve existing protocols and processes to ensure quality and rapid, iterative deployment of software, models and data as a service.

- Refactor and package Python software as a service for popular, broadly used NLP and ML solutions.

- Help data scientists version, test, document and deploy models as a service.

- Develop a process for delivering NLP feature stores/data as a service for downstream data-driven applications.

- Implement and orchestrate version control across all pipeline artifacts.

- Design and use containers to manage Python package dependencies and maintain environmental stability.