Develop and Deploy advanced Generative AI large language models, Machine Learning and Deep Learning Models/algorithms to enhance and/or automate existing business processes with predictive and intelligent decision-making, content aggregation and contextualized insights.
Collaborate with data scientists and data engineers to build production-level models and pipelines, including any required preprocessing of input datasets and postprocessing after model inference.
Processing, cleansing, and verifying the integrity of structured and unstructured business data used for analysis.
Analyze large amounts of information to discover underlying trends and patterns that are relevant for solving business problems. Select features and perform proper data transformation to optimize datasets for building the models.
Evaluate, visualize, and communicate the AI/ML model results and correlation with business KPI’s.
Work in a startup-type environment to design and build innovative applications using Automation, Machine Learning/Cognitive Service, business / functional proofs-of-concepts to scalable, production-ready solutions across a strategic business group
Actively lead, analyze, and recommend highly complex business opportunities through assessments/workshops, detailed data analysis/modeling, and overall end-end solutioning to propose predictive, AI-driven solutions that drive the most business value with sustained impact.
Work within project planning constraints, communicating any identified project risks and issues to the delivery/project manager and provide inputs to the change control process.
Help develop standard operation practices and support the Operations Teams through UAT and after go-live.
Continuously optimize the existing AI/ML operations and help build effective model performance monitoring, alert, and improvement framework to proactively identify problems/issues before business impact.
Requirements & Skills:
Bachelor’s in Computer Science, Data Science, or Engineering fields
4-6 years of IT experience in solution architect/data scientist/software development for large corporate/organizations
Hands-on experience in LLM engineering and LLMOps, including advanced prompt engineering and fine-tuning of LLMs.
3+ years of experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc
3+ years of hands-on experience with Python programming and statistical packages and ML libraries such as scikit-learn, Keras, TensorFlow, etc.
2+ years of experience in building AI solutions with NLP/NLG frameworks such as Keras, TensorFlow, HuggingFace Transformers, and libraries (like NLTK, Spacy, genism)
2+ years of experience working on the data science platform Databricks
2+ years of experience in building IT use cases/solutions, especially around AI/ML cognitive services, based on Cloud infrastructure and services such as Azure cloud platforms and Databricks.
