Machine Learning Engineer

Actively Reviewing the Applications

PAR Technology

India, Rajasthan, Jaipur Full-Time

Posted 16 hours ago • Apply by June 16, 2026

Job Description

For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram.

Machine Learning Engineer

Location: Jaipur / Gurgaon, India

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. In this role, you will design, develop, and scale GenAI-powered services and machine learning infrastructure that power key product features such as campaign recommendations, personalized promotions, and customer intelligence.

This role is ideal for someone who is hands-on, performance-driven, and experienced in productionizing ML systems using modern data platforms such as AWS Bedrock, Databricks, LangChain, and LlamaIndex.

What You’ll Do

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.

What You’ll Need

3+ years of hands-on experience working on production Machine Learning projects.
Master’s or PhD in Computer Science, Machine Learning, AI, or related field.
Strong knowledge of machine learning algorithms, recommendation systems, and NLP.
Hands-on experience with LLM frameworks such as Hugging Face, LangChain, OpenAI, Cohere, or similar.
Strong programming skills in Python with experience in scalable, production-grade system design.
Advanced experience with Databricks, including MLflow, notebooks, pipelines, and job orchestration.
Experience with cloud platforms (AWS preferred), including S3, Lambda, ECS/EKS, SageMaker, and Step Functions.
Experience with modern data platforms such as Delta Lake, Elasticsearch, Redis, NoSQL databases, or columnar storage systems.
Strong communication skills and ability to work effectively with global teams.
Flexibility to collaborate across time zones, including occasional overlap with teams in PST and EST.

Preferred Qualifications

Experience building recommendation systems in hospitality, restaurant, or digital marketing domains.
Experience fine-tuning or building custom LLMs or embedding models.
Experience developing enterprise-scale Text-to-SQL or conversational AI systems.
Experience working with vector databases such as Pinecone, Weaviate, FAISS, or ChromaDB.
Contributions to open-source ML, AI, or GenAI projects.

PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact [email protected]. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.