Senior AI/ML Engineer with Gen-AI

Key Responsibilities:

Architect AI/ML systems as well as integrating AI/ML features into business apps Solution and execute end-to-end Generative AI projects with Open AI, GPT-4, Llama-2 etc 
Experience in data acquisition, data mining, data transformation, cleaning structured/unstructured data, modelling, or machine learning, including at least 1 year in Generative AI. 
Develop end-to-end NLP Deep models Assist in Conversational AI, Information retrieval, Knowledge Management Research and implement appropriate ML algorithms and tools Build and manage Supervised and Unsupervised ML algorithms
Select appropriate datasets and data representation methods, Perform statistical analysis and fine-tuning using test results Utilise AWS Lambda, EC2 Services to build solution and Provide code deployments
Communicate architecture decisions effectively to multiple stakeholders including presenting to client Architecture Review Boards (ARBs).
As a Senior Machine Learning Engineer, you will possess the following essential strengths, skills, and competencies.
Problem-Solving Skills: Strong emphasis on product development.
Communication Skills: Excellent written and oral communication, and strong interpersonal skills.
Independence: Ability to thrive in a fast-paced environment and work independently. Analytical Skills: Experience performing root cause analysis to answer specific business questions.
Programming Languages: Familiarity with Scala (preferred), Python & SQL
Predictive Modelling and Analysis: Experience in machine learning and algorithm development. Mathematical Skills: Solid foundation in statistics, calculus, and linear algebra.
Model Deployment: Experience productizing and deploying machine learning models. Data Warehousing: Experience with data warehouse tools (Snowflake preferred). Data Pipeline Management: Experience with data pipeline and workflow management tools (Airflow preferred). Engineering: Experience in Prompt engineering with LLM Development using Langchain. Semantic Kernel, Open Source/ API based LLMs or similar.
API Development: Experience building scalable APIs in Python (using FastAPI is a plus). · Data Processing: Working knowledge of data processing packages (e.g., numpy, scipy, pandas).