Job Description

Responsibilities:

• Understand the business problem, analyse the data, and define the success criteria
• Work with engineering team and architecture teams for data identification and collection, harmonization, and cleansing for the data analysis and preparation
• Responsible for analysing and identifying appropriate algorithms for the defined problem statement
• Analyse additional data inputs and methods that would improve the results of the models and look for opportunities
• Responsible for building models that are interpretable, explainable and sustainable at scale and meets the business needs.
• Build visualizations and demonstrate the results of the model to the stakeholders and leadership team
• Must be conversant with Agile methodologies and tools and have a track record of delivering products in a production environment.
• Lead the design of prototypes in our AI factory, partnering with product teams, AI strategists, and other stakeholders throughout the AI development life cycle.
• Lead and transform data science prototypes
• Mentor a diverse team of junior engineers in machine learning techniques, tools and concepts. Provides guidance and leadership to more junior engineers.
• Explore and recommend new tools and processes which can be leveraged across the data preparation pipeline for capabilities and efficiencies.
• Ensure that our development and deployment are tightly integrated to each other to maximize the deployment user experience.
• Curator for all code and binary artifact repositories (containers, compiled code).
• Work with AI strategists, DevOps, data engineers/SMEs from domain to understand how data availability and quality affects model performance.
• Evaluate open source and proprietary technologies and present recommendations to automate machine learning workflows, model training and versioned experimentation, digital feedback and monitoring.
• Develop and disseminate innovative techniques, processes and tools, that can be leveraged across the AI product development lifecycle.

Qualifications:

• Experience building ML models in a modern cloud-based architecture
• 5+ years of demonstrated experience in developing highly scalable, reliable, and resilient multi-tenanted ML algorithms for large scale use cases in Sales and Marketing, Revenue management, Supply Chain and other business areas.
• 5+ years of demonstrated experience in developing ML pipelines on various frameworks on AWS, Azure, or similar cloud platforms.
• Proficient and experienced in Python and SQL for data analysis and exploration
• Experience in cloud based solutioning and managing enterprise grade end to end machine learning solutions with automated pipelines for data processing, feature engineering, training, evaluation, deployment, integration and monitoring.
• Hands-on experience with Docker, Kubernetes and the cloud infra like Azure, AWS, GCP and on machine learning tools like Azure Machine Learning, Amazon Sagemaker, MLFlow, KubeFlow, etc in production.
• Experience in building end to end Machine Learning Architectures.
• Strong knowledge in one of machine learning design principles, ML Ops best practices or Big Data architectures.
• Experience in end-to-end AI life cycle including Data science, technical experience in AI, machine learning, predictive modelling, Natural Language Processing (NLP), Deep learning, advanced analytics and statistics modelling, Python, SQL, Azure/AWS/GCP
• Experience on model monitoring, explainability, model management, version tracking & storage and AI governance
• Deployment of models, Docker, ML Pipelines, Azure Machine Learning
• Knowledge on SQL/NoSQL databases, microservices and REST APIs, docker
• Strong Knowledge on source code management, configuration management, CI/CD, security and performance.
• Ability to look ahead to identify opportunities and thrive in a culture of innovation
• Self-starter who can see the big picture, and prioritize your work to make the largest impact on the business’ and customer’s vision and requirements
• Experience in building, testing, and deploying code to run on Azure cloud datalake
• Ability to Lead/nurture/mentor others in the team.
• A can-do attitude in anticipating and resolving problems to help your team to achieve its goals.

Must have experience in Agile development methods

Global VISA and Relocation Specifications:

Primary Location

IT Centre Bengaluru GDTC

Additional Locations

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time