Machine Learning Engineer at Par%20technology

About the Role

PAR is looking for a technically exceptional Machine Learning Engineer to join our AI team and help shape the next generation of personalized customer engagement products. This role focuses on designing, developing, and scaling GenAI-powered services and machine learning infrastructure that power key product features such as campaign recommendations, personalized promotions, and customer intelligence.

Key Responsibilities

• →Design, develop, and deploy GenAI-powered microservices and recommendation systems using LLMs, embedding models, and Retrieval-Augmented Generation (RAG).
• →Build scalable data pipelines using Databricks, PySpark, and Delta Lake for model training, feature engineering, and real-time or batch inference.
• →Develop and maintain high-performance ML APIs using FastAPI, Flask, or similar frameworks.
• →Implement retrieval pipelines using vector databases such as FAISS, ChromaDB, or Pinecone to enable hybrid search and personalization.
• →Collaborate closely with product, engineering, and data teams to integrate ML capabilities into customer-facing applications and dashboards.
• →Implement ML Ops best practices including model versioning, evaluation, monitoring, and automated retraining using MLflow or similar tools.
• →Design and maintain CI/CD workflows for ML pipelines using tools such as GitHub Actions, Databricks Repos, or similar.
• →Contribute to architectural decisions around LLM orchestration, multi-model systems, and infrastructure optimization on AWS.
• →Communicate technical solutions clearly and provide actionable recommendations to cross-functional stakeholders.