We are looking for an Senior AI Engineer to be part of our Global Data Science and Innovation team.
As part of a high-profile team, the position offers a unique opportunity to work first-hand on some of the most exciting, and challenging AI-led projects within the organization, and be part of a fast-paced, entrepreneurial environment. As a senior member of the team, you will be responsible for working with your leadership team to build a world-class portfolio of AI-led solutions within KANTAR leveraging the latest developments in AI/ML.
You will be part of several initiatives to productionize multiple R&D PoCs and pilots that leverage a variety of AI/ML algorithms and technologies, particularly using (but not restricted to) Generative AI. As an experienced AI engineer, you will hold yourself accountable for the entire process of developing, scaling, and commercializing these enterprise-grade products and solutions. You will be working hands-on as well as with a team of highly talented cross-functional, geography-agnostic team of data scientists and AI engineers.
As part of the global data science and innovation team, you will be a representative and ambassador for data science/AI/ML led solutions with internal and external stakeholders.
Job Description
Candidate will be responsible for the following:
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Develop and maintain scalable and efficient AI pipelines and infrastructure for deployment.
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Deploy AI models and solutions into production environments, ensuring stability and performance.
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Monitor and maintain deployed AI systems to ensure they operate effectively and efficiently.
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Troubleshoot and resolve issues related to AI deployment, including performance bottlenecks and system failures.
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Optimize deployment processes to reduce latency and improve the scalability of AI solutions.
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Implement robust version control and model management practices to track AI model changes and updates.
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Ensure the security and compliance of deployed AI systems with industry standards and regulations.
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Provide technical support and guidance for deployment-related queries and issues.
Qualification, Experience, and skills
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Advanced degree from top tier technical institutes in relevant discipline
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4 to 10 years experience, with at least past few years working in Generative AI
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Prior firsthand work experience in building and deploying applications on cloud platforms like Azure/AWS/Google Cloud using serverless architecture
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Proficiency in tools such as Azure machine learning service, Amazon Sagemaker, Google Cloud AI
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Prior experience with containerization tools (for ex., Docker, Kubernetes), databases (for ex., MySQL, MongoDB), deployment tools (for ex., Azure DevOps), big data tools (for ex.,Spark).
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Ability to develop and integrate APIs. Experience with RESTful services.
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Experience with continuous integration/continuous deployment (CI/CD) pipelines.
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Knowledge of Agile working methodologies for product development
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Knowledge of (and potentially working experience with) LLMs and Foundation models from OpenAI, Google, Anthropic and others
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Hands on coding experience in Python
Desired skills that would be a distinct advantage
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Preference given to past experience in developing/maintaining live deployments.
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Comfortable working in global set-ups with diverse cross-geography teams and cultures.
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Energetic, self-driven, curious, and entrepreneurial.
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Excellent (English) communication skills to address both technical audience and business stakeholders.
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Meticulous and deep attention to detail.
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Being able to straddle big picture and details with ease.
