You will be part of the IT Information Management & Analytics team and in this role, you will at the forefront of implementing state-of-the-art Generative AI, Machine Learning and AI Cognitive Services enhanced business use cases. This Advanced AI Engineer role will work with the business stakeholders, IT business partners, functional consultants, and infrastructure/technology teams to deliver innovative AI technology solutions that accelerate digital transformation and drive operational efficiency as well as business growth. You will focus primarily on the full cycle delivery of AI/ML use cases from requirements/design to release, driving the evolution of AI/ML infrastructure/process, and enabling Intelligent Apps & Automation, next generation of AI Copilots/Assistants, etc.
KEY RESPONSIBILITIES
· Collaborating with multi-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.
· Conducting research to stay up to date with the latest advancements in generative AI, machine learning, and deep learning techniques and find opportunities to integrate them into our products and services.
· Optimizing existing generative AI models for improved performance, scalability, and efficiency.
· Engineer prompts and optimize few-shot techniques to enhance LLM's performance on specific tasks.
· Evaluate LLM's zero-shot and few-shot capabilities, fine-tuning hyper-parameters, ensuring task generalization, and exploring model interpretability for robust web app integration.
· Collaborate with ML and Integration engineers to demonstrate LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app.
· Be a proactive partner to your business stakeholders and provide insights.
· Tackle business-critical questions by developing and testing hypotheses, and aid evidence-based decision making.
· Partner with Product Managers, Data Engineers, Data Scientists, and Business Stakeholders to drive business decisions and product roadmaps.
· BTech/Master’s in engineering/Technology or MSc with 4-6 years of relevant experience or PhD with 3+ years’ experience.
· Problem solver at heart with experience in Machine learning, Data Science and Statistics.
· Proficiency with Python, PySpark, BigQuery, SQL
· Proficiency with ML libraries Sklearn, Pytorch ,Tensorflow, Spark MLlib
· Cloud friendliness (AWS /Azure) to leverage distributed computing/scalability.
· Experience in Deep Learning and classical Machine Learning, including but not limited to CNN/RNN architectures, Reinforcement learning, Graph Neural networks, OpenCV
PREFERRED
· Proficient in Python and have experience working with machine learning and NLP processing techniques and tools.
· Worked on Vector DB and SQL databases: MongoDB, PostgreSQL, SQL Server
· Solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.
· Proficient in Langchain, LLMs
· Strong knowledge of data structures, algorithms, and software engineering principles.
· Tools you may use include Azure services such as Azure Machine Learning and Azure prompt flow, as well as python, Langchain, Streamlit, docker, git, and elastic search.