
Senior AI/ML Engineer
3 weeks ago
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.
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