Data Science
Machine Learning (ML)
Python
- 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
Subodh Popalwar
Software Engineer, Memorres
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Software Engineer, Memorres