2 days ago
Bengaluru, IndiaSenior
Responsibilities
- Collect, transform, explore, and assess data from disparate sources for AI model construction.
- Design, build, document, maintain, and industrialize AI/ML models that automate and improve operational efficiency.
- Evaluate dataset bias and flaws and ensure training and validation reflect operational requirements.
- Research methods to improve AI robustness, explainability, trustworthiness, and performance.
- Develop software prototypes, interactive dashboards, technical reports, presentations, and storytelling materials to communicate AI capabilities.
- Collaborate with domain experts, external partners, software development teams, and international stakeholders.
- Develop AI-based RAG applications and support generative AI and LLM initiatives.
- Contribute to AI publications, projects, conferences, events, and training sessions.
- Implement testing strategies, debug solutions, and deliver models according to quality, cost, schedule, and customer requirements.
Requirements
- Degree in artificial intelligence, computer science, or engineering, supplemented by extensive training in data science and AI or related disciplines.
- At least 8 years of experience in data science and AI.
- Excellent knowledge of Python programming and the Python data science stack, including technologies such as pandas, scikit-learn, Keras, NumPy, TensorFlow, PyTorch, and OpenAI.
- Strong knowledge of artificial intelligence and machine learning algorithms, including classification, regression, dimensionality reduction, Bayesian models, NLP, neural networks, and deep learning.
- Experience with the Microsoft Azure cloud platform and cloud services such as PaaS, SaaS, and serverless functions.
- Familiarity with LLM architectures and models such as BERT, GPT-4, Llama 2, and Mistral.
- Knowledge of generative AI frameworks such as Hugging Face and LlamaIndex.
- Experience developing AI-based RAG applications; experience with knowledge RAG applications is desirable.
- Desirable experience with generative AI and LLM fine-tuning, including supervised fine-tuning and reinforcement learning.
- Desirable familiarity with knowledge-graph data modeling and graph database technologies and with developing safe and trustworthy AI applications.
- Proven record of delivering high-quality AI-oriented solutions, including testing and debugging strategies.
- Fluent English and strong communication, presentation, organizational, planning, and collaboration skills.
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