AI Product Development: Drive end-to-end development of AI/ML and GenAI solutions, including data ingestion, feature engineering, modeling, deployment, testing, and performance monitoring
Advanced Modeling: Build and optimize machine learning and deep learning models across domains such as NLP, NLU and multidimensional time-series forecasting
GenAI Optimization: Implement quantization and optimization techniques for LLMs and GenAI models to improve efficiency and reduce cost
Lifecycle Management: Develop the full lifecycle of NLP and ML models for a suite of products, ensuring compliance with enterprise governance and Responsible AI standards
Proof-of-Concept Leadership: Execute large-scale PoCs leveraging on-premise and cloud technologies to validate innovative AI solutions for complex systems (Preferably IT Asset Management)
RAG & Vector DB Pipelines: Design and implement retrieval-augmented generation (RAG) pipelines with vector databases to enable accurate, context-aware responses
Governance & Best Practices: Establish and enforce best practices for ML, DL, and GenAI development, ensuring rigor, reproducibility, and quality outcomes
Cross-Functional Collaboration: Partner with business stakeholders, compliance teams, and platform engineering to align AI initiatives with organizational goals
Autonomous Problem-Solving: Operate with a high degree of independence to tackle complex technical and business challenges
Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
Required Qualifications:
Undergraduate degree or equivalent experience
Proven experience in ML, NLP, and GenAI product development
Hands-on expertise with RAG architectures, vector databases, and LLM fine-tuning
Solid knowledge of model optimization techniques (e.g., quantization, distillation)
Proficiency in MLOps tools and practices for model deployment and monitoring
Job Classification
Industry: RetailFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Technical LeadEmployement Type: Full time