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Sr. AI / ML Engineer

Sr. AI / ML Engineer

SoulaxKollam, IN
11 hours ago
Job description

Sr AI / ML Engineer :

We’re looking for a Senior AI / ML Engineer with a strong foundation in geometric reasoning, hands-on Python and SQL expertise, and a flair for creative problem-solving. This role is ideal for someone who thrives on building innovative, agent-driven solutions and can independently devise new frameworks or approaches to solve complex problems.

Roles & Responsibilities :

  • Develop, optimize, and deploy end-to-end ML models with strong Python and SQL expertise .
  • Apply linear algebra, calculus, probability, and statistics to solve real-world ML problems.
  • Holds a strong understanding of Computer Vision methodologies and its practical applications.
  • Design and implement ML algorithms such as Linear / Logistic Regression, Trees, XGBoost, Clustering, and Anomaly Detection.
  • Build scalable, agent-driven AI solutions with a focus on innovation and independent problem-solving.
  • Strong experience in geometric concept application and hands-on coding over theoretical research.
  • Practice Test-Driven Development with exposure to AWS cloud deployment.
  • Collaborate cross-functionally as a senior developer, driving creative and practical AI / ML engineering solutions.

Required Skills :

  • Proven experience as a hands-on Senior Developer or AI / ML Engineer (Ph.D. not mandatory, but strong experience and creativity are key).
  • Strong background in Python programming and SQL.
  • Demonstrated ability to creatively solve problems and think beyond standard solutions.
  • Experience designing or implementing agent-driven architectures or frameworks.
  • Ability to work independently and drive innovation.
  • Familiarity with test-driven development (TDD) practices.
  • Experience with AWS cloud platforms is a plus.
  • Exposure to geometric computation, simulations, or 3D spatial reasoning is a strong advantage.
  • Nice to Have :

  • Experience with reinforcement learning or autonomous agents.
  • Familiarity with modern ML Ops practices.
  • Previous work in a research-heavy or innovation-focused environment.
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