AI Architect

Qualifications

Bachelor’s/Masters degree in Computer Science, MIS, Business Management, or related field required 15+ years proven experience in programming and development projects. Hands-on experience with software development and system administration

• At least 10-12 years hands-on programming experience working on enterprise products. Demonstrated proficiency in multiple programming languages with a strong foundation in a statistical platform such as Python, R, SAS, or MatLab. Experience building AI models in platforms such as Keras, TensorFlow, or Theano. Demonstrated commitment to learning about AI through your own initiatives through courses, books, or side projects.
• Excellent drive Ability to work in ambiguous situations Problem-solving aptitude Strong communication skills Understand sometimes ambiguous, needs, and translate to clear, aligned requirements
• Ability to work with virtual teams (remote work locations); lead team of technical resources (employees and contractors) based in multiple locations across geographies Positive attitude Participate in ideation and solutioning discussions, driving clarity of complex issues/requirements to build robust solutions

Key Skills

· Hands on experience with building language models, machine learning and AI models leveraging industry tools, products, and Azure cognitive services.

• Flask / Django / Fast API development expertise with least 2-3 project delivered as a developer.
• Core Python - Iterators, Generators , OOP concepts, Python Shell (REPL) and Object Relational Mapper, Data structure and Exception handling etc.
• Complex Scenario Knowledge : Contemporary Python Libraries for LM orchestration e.g.LangChain / Llamaindex and Autogen etc.
• Good to have at least one of the env : Azure or AWS expertise in terms of building and deploying AI apps using cloud services

· Deep and hands-on expertise in (as an individual contributor) Undertaking data collection, Data mining, preprocessing and analysis of structured and unstructured data.

· Hands-on expertise in large language models (LLMs/LSTMs/BERT) that can perform complex reasoning in few- and zero-shot settings by generating intermediate chain of thought (CoT) reasoning steps e.g.

· Experience of building / customizing and fine-tuning AI models including LLM models via OpenAI studio extended through AzureOpenAIcognitive services for rapid PoCs

· Programming Skills - knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.

· Deep and hands-on experience in applying machine learning algorithms.

· Strong data science and data engineering background both with open source and cloud distributed machines learning and AI tools especiallyAzure Cognitive Services and Azure Machine Learning

• Strong understanding of Azure cloud technology including Cognitive Servicesviz. Vision, Speech, Language, Decision, Search and Azure OpenAI and its implementation

· Proven experience with, and applied knowledge of, at least one scripting language, such as Python, or Deep expertise in building and fin-tuning large language models of OpenAI e.g. GPT 4, GPT 3.5, DALL-E, Whisper, Embeddings, Moderation, and Codex etc.

· Expertise in completions, embeddings, edits, transcriptions, translations, fine-tunes, and moderations across the several large language models especially those of OpenAI

· Hands-on training and fine-tuning experience with Azure OpenAI distributed OpenAI models such as DaVinci, curie, Babbage, ADA

Responsibilities

• Independently build and demo rapid generative AI demos and solutions with short notices
• Serve as lead data strategist/scientist/engineer to identify and integrate new datasets that can be leveraged through our product capabilities, and work closely with the engineering team in the development of data products with Azure Cognitive Services (especially AzureOpenAI)
• Build AI and ML models for generative AI applications with ChatGPT
• Transforming natural language data into useful features using NLP/NLG/LLM techniques to feed classification algorithms.
• Work with several generative AI tools,stacks and products (primarily Azure OpenAI) to quickly build and roll-out multiple use PoCs and MVPs
• Identify valuable data sources and automate collection processes.
• Undertake preprocessing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns.
• Build predictive models and machine-learning algorithms.
• Combine models through ensemble modeling.
• Present information using data visualization techniques.