AI Innovation Lead

2 days ago

Bengaluru, Karnataka, India beBeeArtificial Full time ₹ 1,80,00,000 - ₹ 2,50,00,000

Job Title: AI Innovation Lead

We are seeking a passionate and analytical individual to lead the development of cutting-edge AI solutions for meaningful societal challenges.

Key Responsibilities:

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  • Design, develop, implement, test, and maintain scalable and efficient software solutions.
  • Leverage extensive knowledge about large language models (LLMs) to create scalable, intelligent solutions for content understanding and user engagement on products in social impact space across a wide range of domain areas.
  • Drive data-driven experimentation using A/B testing, advanced analytics, and statistical techniques to identify growth opportunities and refine algorithms.
  • Develop and optimize pipelines, tools, and infrastructure.
  • Mentor team members and foster collaboration and high-performance culture within cross-functional teams, including engineers, product managers, researchers, and designers.
  • Stay informed on emerging trends in AI and machine learning and integrate them to drive innovation and improve product offerings.
  • Define project scopes, objectives, and timelines, and ensure successful execution of engineering projects from conception to deployment.

Required Skills and Qualifications:

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  • Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
  • 7-8 years of hands-on experience technical engineering experience with coding in languages including, but not limited to, C, Golang, C#, Java, JavaScript, or Python.
  • Proficiency and experience in embedding models, query models including but not limited to n8n, Potpie, Langraph, LlamaIndex and similar frameworks.
  • Familiarity with LLMs (e.g., OpenAI, Ollama, Mistral, Gemini) and RAG-based architectures.
  • Demonstrated success in working with large datasets and cloud platforms such as AWS, GCP, or Azure.
  • Experience in leveraging multi modal, multi-channel inputs with familiarity in data modelling, database management, and data storage in vector stores, file containers, graph databases, and relational structures.
  • Familiarity with Model Deployment and MLOps.
  • Deployment tools and frameworks and packaging models as Docker containers.
  • MLOps practices including ML lifecycle orchestration.
  • Good communication and problem-solving skills with a collaborative mindset.

Benefits:

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  • Work with leading researchers from top institutions.
  • Build cutting-edge AI solutions for meaningful societal challenges.
  • Access to state-of-the-art infrastructure and tools.
  • Be part of a purpose-driven, collaborative, and innovative environment.

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