AI Technical Lead

1 day ago

Mumbai, Maharashtra, India beBeeArtificial Full time US$ 2,00,000 - US$ 2,50,000
Job Overview:

We are seeking an experienced AI Lead to drive the development and deployment of cutting-edge AI/ML solutions across the organization. As a key member of our team, you will work closely with business stakeholders, data scientists, engineers, and product teams to design scalable, ethical, and impactful AI models.

You will lead the design, development, and deployment of ML/AI models (classification, NLP, computer vision, recommender systems, etc.) while ensuring production-grade model performance, latency, accuracy, and interpretability. You will integrate AI models into existing systems using MLOps best practices.

The ideal candidate will be able to architect end-to-end ML pipelines: data ingestion, preprocessing, model training, evaluation, and monitoring. You will utilize modern AI frameworks and cloud platforms for scalable AI deployments.

Additionally, you will mentor junior data scientists and engineers, conduct code reviews, knowledge sharing, and promote AI best practices. You will collaborate with cross-functional teams to translate requirements into technical solutions and communicate AI concepts and ROI to non-technical stakeholders.

Key Responsibilities:
  • AI Strategy & Leadership:
    • Define and execute the AI roadmap aligned with business objectives.
    • Identify and evaluate AI use cases across business units.
    • Present solution architectures, POCs, and business impact assessments to leadership.
  • Model Development & Deployment:
    • Lead the design, development, and deployment of ML/AI models.
    • Ensure production-grade model performance, latency, accuracy, and interpretability.
    • Integrate AI models into existing systems using MLOps best practices.
  • Technical Expertise:
    • Architect end-to-end ML pipelines: data ingestion, preprocessing, model training, evaluation, and monitoring.
    • Apply modern AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain, etc.).
    • Utilize cloud platforms (AWS/GCP/Azure) for scalable AI deployments.
  • Team Management & Mentorship:
    • Mentor and guide junior data scientists and engineers.
    • Conduct code reviews, knowledge sharing, and promote AI best practices.
    • Build a strong AI culture within the team.
  • Stakeholder Engagement:
    • Collaborate with product, engineering, and business teams to translate requirements into technical solutions.
    • Communicate AI concepts and ROI to non-technical stakeholders.

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