2 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Collect, transform, explore, and combine data from disparate sources for AI model construction.
- Identify dataset biases and flaws and ensure training and validation designs reflect operational needs.
- Design, build, document, manage, and sustain AI/ML models for automation and operational efficiency.
- Research methods that improve the robustness, explainability, and trustworthiness of AI/ML algorithms.
- Develop AI-based generative AI and RAG applications, including support for LLM architectures and models.
- Create prototypes, presentations, interactive dashboards, technical reports, and other materials to communicate AI capabilities.
- Collaborate with domain experts, external partners, software development teams, and international teams to industrialize AI solutions.
- Participate in conferences, publications, AI community projects, and AI training sessions.
- Implement testing strategies, debug solutions, and deliver models according to quality, cost, schedule, and customer requirements.
Requirements
- A 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.
- Excellent knowledge of Python programming and the Python data science ecosystem.
- Knowledge of modern statistics, text mining, image processing, NLI, NLP, and NLU.
- Experience with Microsoft Azure and cloud services including PaaS, SaaS, REST APIs, and serverless functions.
- Strong knowledge of artificial intelligence and machine learning algorithms, including classification, regression, dimensionality reduction, Bayesian models, NLP, neural networks, and deep learning.
- 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 using Agile-based principles and tools.
- 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.
- Desirable experience developing AI-based knowledge RAG applications and safe, trustworthy AI applications.
- A proven track record delivering high-quality AI-oriented solutions, with strong organizational, planning, communication, and presentation skills.
- Fluent English and willingness to work with local, remote, and international teams.
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