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MLOps Engineer (3-5 yrs)

3-5 years

MLOps Engineer (3-5 yrs)

Talent Socio

posted 4d ago

Job Role Insights

Flexible timing

Job Description

Responsibilities :


- Develop, productionize, and deploy scalable, resilient software solutions to integrate and operationalize AI and ML capabilities.


- Adhere to software architecture and software design best practices to write scalable, maintainable, well-designed code.


- Develop automated end-to-end ML delivery pipelines; enabling model training, evaluation, tracking, and serving.


- In collaboration with Data Engineering, design and build feature engineering pipelines for extraction, transformation, and loading of data from a variety of data sources for ML models.


- Advocate for AI security and responsibility best practices. Enable monitoring and observability capabilities for the delivery teams.


- Stay current on new developments in ML frameworks, tooling, data modeling, software architecture, and libraries available for solution development.


- Coach data scientists and data engineers on software development best practices.


- Agile Project Work.


- Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate AI and MLOps solutions.


- Act as a positive champion for broader organizations to develop a stronger understanding of software design patterns that deliver scalable, maintainable, well-designed analytics solutions.


- Acts as an expert on complex technical topics that require cross-functional consultation.


Requirements :


- Experience applying continuous delivery best practices, including CI/CD, Version Control, Trunk Based Development, Release Management, and Test-Driven Development using popular tooling (e. g., Azure DevOps, CircleCI).


- Experience deploying and operating scalable, reliable, and secure software solutions on modern clouds (AWS, Azure, GCP) and container platforms (Docker, Kubernetes, etc. ).


- Knowledge of Machine Learning lifecycle (wrangling data, model selection, model training, modeling validation, drift monitoring, and deployment at scale) and experience working with data scientists.


- Familiar with cloud data warehousing solutions such as Snowflake, BigQuery, Fabric, etc.


- Experience with popular MLOps tools (e. g., Kubeflow, MLflow, AzureML, Domino).


Preferred :


- Experience with deep learning platforms and frameworks (e. g. TensorFlow, Keras, etc. ).


- Experience working in Data Architecture, engineering, and ETL teams, managing implementation of projects that utilize big data, advanced analytics, and machine learning technologies.


- Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking to large audiences.


- Demonstrated experience in teaching and/or mentoring profile.


Functional Areas: Other

Read full job description

What people at Talent Socio are saying

What Talent Socio employees are saying about work life

based on 11 employees
89%
67%
72%
100%
Flexible timing
Alternate Saturday off
No travel
Day Shift
View more insights

Talent Socio Benefits

Work From Home
Job Training
Cafeteria
Team Outings
Free Transport
Child care +6 more
View more benefits

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