MLops Lead Engineer

A analytics consulting start-up

MLops Lead Engineer

InvokHR

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MLops Lead Engineer

at A analytics consulting start-up

Agency job

via InvokHR

7 - 12 yrs

₹10L - ₹15L / yr

Remote only

Skills

Machine Learning (ML)

Data Science

MS-Office

Artificial Intelligence (AI)

Python

CI/CD

DevOps

A Data and MLOps Engineering lead that has a good understanding of modern Data engineering frameworks with a focus on Microsoft Azure and Azure Machine Learning and its development lifecycle and DevOps.
Aims to solve the problems encountered when turning Data into meaningful solutions using transformations and data science code into production Machine Learning systems. Some of these challenges include:
- ML orchestration - how can I automate my ML workflows across multiple environments
- Scalability - how can I take advantage of the huge computational power available in the cloud?
- Serving - how can I make my ML models available to make predictions reliably when needed?
- Monitoring - how can I effectively monitor my ML system in production to ensure reliability? Not just system metrics, but also get insight into how my models are performing over time
- Reuse – how can I profess reuse of artefacts built and establish templates and patterns?

The MLOps team works closely with ML Engineering and DevOps teams. Rather than focus just on individual use cases, the focus would be to specialise in building the platforms and tools that can help adoption of MLOps across the organisation and develop best practices and ways of working to develop a state of the art MLOps capability.

A good understanding of AI/Machine Learning and software engineering best practices such as Cloud Engineering, Infrastructure-as-Code, and CI/CD.

Have excellent communication and consulting skills, while delivering innovative AI solutions on Azure.

Responsibilities will include:

Building state-of-the-art MLOps platforms and tooling to help adoption of MLOps across organization
Designing cloud ML architectures and provide a roadmap for flexible patterns
Optimizing solutions for performance and scalability
Leading and driving the evolving best practices for MLOps
Helping to showcase expertise and leadership in this field

Tech stack

These are some of the tools and technologies that we use day to day. Key to success will be attitude and aptitude with a vision to build the next big thing in AI/ML field.

Python - including poetry for dependency management, pytest for automated testing and fastapi for building APIs
Microsoft Azure Platform - primarily focused on Databricks, Azure ML
Containers
CI/CD – Azure DevOps
Strong programming skills in Python
Solid understanding of cloud concepts
Demonstrable interest in Machine Learning
Understanding of IaC and CI/CD concepts
Strong communication and presentation skills.

Remuneration: Best in the industry

Connect: https://www.linkedin.com/in/shweta-gupta-a361511

A Data and MLOps Engineering lead that has a good understanding of modern Data engineering frameworks with a focus on Microsoft Azure and Azure Machine Learning and its development lifecycle and DevOps.
Aims to solve the problems encountered when turning Data into meaningful solutions using transformations and data science code into production Machine Learning systems. Some of these challenges include:
- ML orchestration - how can I automate my ML workflows across multiple environments
- Scalability - how can I take advantage of the huge computational power available in the cloud?
- Serving - how can I make my ML models available to make predictions reliably when needed?
- Monitoring - how can I effectively monitor my ML system in production to ensure reliability? Not just system metrics, but also get insight into how my models are performing over time
- Reuse – how can I profess reuse of artefacts built and establish templates and patterns?

Responsibilities will include:

Building state-of-the-art MLOps platforms and tooling to help adoption of MLOps across organization
Designing cloud ML architectures and provide a roadmap for flexible patterns
Optimizing solutions for performance and scalability
Leading and driving the evolving best practices for MLOps
Helping to showcase expertise and leadership in this field

Tech stack

These are some of the tools and technologies that we use day to day. Key to success will be attitude and aptitude with a vision to build the next big thing in AI/ML field.

Python - including poetry for dependency management, pytest for automated testing and fastapi for building APIs
Microsoft Azure Platform - primarily focused on Databricks, Azure ML
Containers
CI/CD – Azure DevOps
Strong programming skills in Python
Solid understanding of cloud concepts
Demonstrable interest in Machine Learning
Understanding of IaC and CI/CD concepts
Strong communication and presentation skills.

Remuneration: Best in the industry

Connect: https://www.linkedin.com/in/shweta-gupta-a361511

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