Senior AI/ML Technical Lead

2 days ago

Ghaziabad, Uttar Pradesh, India beBeeInnovator Full time ₹ 1,80,00,000 - ₹ 2,50,00,000

AI Innovator

A forward-thinking AI solutions provider is pioneering cutting-edge technology to tackle complex challenges and drive intelligent innovation. We are seeking a highly creative Senior AI/ML Engineer to join our dynamic team.

This role requires an individual with strong problem-solving skills, hands-on experience in designing agent-driven architectures, and the ability to think beyond standard libraries. The ideal candidate will leverage mathematical foundations in linear algebra, calculus, probability, and statistics to solve challenging machine learning problems.

Key Responsibilities:

  • Design, develop, optimize, and deploy robust ML models and pipelines into production using Python and SQL expertise.
  • Architect and implement innovative, scalable, agent-driven AI solutions.
  • Apply geometric computation and 3D spatial reasoning to unique problem domains.
  • Implement various ML algorithms, including Linear/Logistic Regression, Tree-based models (XGBoost), Clustering, and Anomaly Detection.
  • Drive software excellence through Test-Driven Development (TDD) and contribute to cloud-native AWS infrastructure.
  • Collaborate as a senior technical member, driving projects from conception to deployment.

Required Skills:

  • 5+ years of proven experience as a hands-on Senior AI/ML Engineer or Senior Developer.
  • Expert-level proficiency in Python and SQL.
  • A demonstrated portfolio of creative problem-solving and the ability to independently devise new approaches.
  • Hands-on experience in designing or implementing agent-driven architectures or frameworks.
  • Solid familiarity with Test-Driven Development (TDD) practices.
  • Experience with deploying models on cloud platforms; AWS is highly preferred.
  • Strong background in applying geometric concepts, simulations, or spatial reasoning through code.

Nice to Have:

  • Experience with reinforcement learning (RL) or autonomous agents.
  • Familiarity with modern MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, SageMaker).
  • A background in a research-heavy or innovation-focused environment.

We are shaping the future of AI together.

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