Location : HiTech City,Hyderabad

Working days : 5days from office

Years of exp is 5+yrs

Notice Period : immediate joiners only

Ph.D is an added advantage.

Were 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.

- 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.

- Implement Time Series Forecasting and advanced ML frameworks in production-ready systems.

- 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.