What you will do:
- Team Leadership:
- Lead, mentor, and inspire a team of data scientists, fostering a culture of collaboration and continuous improvement.
- Technical Strategy & Execution:
- Architect and implement scalable machine learning systems from ideation to production. Develop advanced statistical models and optimization algorithms to solve complex business problems.
- Client & Stakeholder Engagement:
- Act as a technical advisor for client projects by translating business requirements into actionable data science solutions.
- Operational Excellence:
- Drive best practices in MLOps, including the effective use of feature stores, model registries, and evaluation frameworks, to ensure the reliability and efficiency of AI systems.
- Pre-sales guidance:
- Support presales efforts by providing technical insights and strategic recommendations.
The ideal candidate should possess:
- Strong foundation in mathematics, statistics, and operations research
- Proven experience deploying AI and machine learning solutions in production environments.
- Hands-on expertise in search algorithms, deep learning, and natural language processing (NLP).
- Demonstrated leadership skills and effective stakeholder management.
- Familiarity with MLOps practices and tools is a plus.
- Excellent problem-solving abilities and clear communication skills
- Familiarity with vector databases, chunking, reranking, MLFlow, feature store, model registry, MLOps, GenAIOps
- Ragas, Promptfoo, DeepEval, LLM as judge
- OptAPlanner, TimeFold
- pandas, Scikit learn, XGBoost, SeaBorn, Numpy
- PyTorch, TensorFlow
- SQL, Spark
- Jupyter notebook
- coding, system design
