over 2 years ago
Delhi, IndiaStaff+
Responsibilities
- Design and develop ensembles of classical and deep learning algorithms for complex enterprise interactions.
- Design and implement statistical models for enterprise cybersecurity risk.
- Apply data-mining, AI, graph analysis, relevance, and recommendation techniques to product problems.
- Build production-quality solutions balancing complexity and performance.
- Participate in the engineering lifecycle by designing ML infrastructure and data pipelines, writing production code, conducting code reviews, and collaborating with infrastructure and reliability teams.
- Drive the architecture and use of open-source numerical computation and machine learning libraries.
- Collaborate with data engineering, frontend, product management, and DevOps teams while documenting work and facilitating teamwork.
Requirements
- Ph.D. or M.S. in Computer Science or Electrical Engineering with hands-on software engineering experience.
- At least 5 years of experience in machine learning and Python programming.
- Expertise in programming concepts and building large-scale systems.
- Knowledge of state-of-the-art algorithms, statistical analysis, and modeling.
- Strong understanding of NLP, probabilistic graphical models, deep learning with graph structures, and model explainability.
- Foundational knowledge of probability, statistics, and linear algebra.
- Ability to handle complex and ambiguous problems, learn quickly, iterate, and take ownership.
- Product focus, collaboration skills, strong communication, and interest in building usable systems.
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