Machine Learning Engineer

Location

Employment Type

Location Type

Department

Position Description:

We are seeking a Machine Learning Engineer to join our growing AI team at PAR. This role will focus on developing and scaling GenAI-powered services, recommender systems, and ML infrastructure that fuel personalized customer engagement. You will work across teams to drive technical excellence and real-world ML application impact.

Position Location:

Jaipur / Gurgaon

Reports To:

[Hiring Manager Title – e.g., Head of AI or Senior Director, AI Engineering]

What We’re Looking For:

Entrees (Requirements):

• Master’s or PhD in Computer Science, Machine Learning, or a related field
• 3+ years of experience delivering production-ready machine learning solutions
• Deep understanding of ML algorithms, recommender systems, and NLP
• Experience with LLM frameworks (Hugging Face Transformers, LangChain, OpenAI API, Cohere)
• Strong proficiency in Python, including object-oriented design and scalable architecture
• Advanced expertise in Databricks: notebooks, MLflow tracking, data pipelines, job orchestration
• Hands-on experience with cloud-native technologies – preferably AWS (S3, Lambda, ECS/EKS, SageMaker)
• Experience working with modern data platforms: Delta Lake, Redis, Elasticsearch, NoSQL, BigQuery
• Strong verbal and written communication skills to translate technical work into business impact
• Flexibility to collaborate with global teams in PST/EST time zones when required

With a Side of (Additional Skills):

• Familiarity with vector databases (FAISS, ChromaDB, Pinecone, Weaviate)
• Experience with retrieval-augmented generation (RAG) and hybrid search systems
• Skilled in deploying ML APIs using FastAPI or Flask
• Background in text-to-SQL applications or domain-specific LLMs
• Knowledge of ML Ops practices: model versioning, automated retraining, monitoring
• Familiarity with CI/CD for ML pipelines via Databricks Repos, GitHub Actions, etc.
• Contributions to open-source ML or GenAI projects
• Experience in the restaurant/hospitality tech or digital marketing domain

Unleash Your Potential: What You Will Be Doing and Owning:

• Build and deploy GenAI-powered microservices and personalized recommendation engines
• Design and manage Databricks data pipelines for training, feature engineering, and inference
• Develop high-performance ML APIs and integrate with frontend applications
• Implement retrieval pipelines with vector DBs and search engines
• Define and maintain ML Ops workflows for versioning, retraining, and monitoring
• Drive strategic architectural decisions for LLM-powered, multi-model systems
• Collaborate across product and engineering teams to embed intelligence in customer experiences
• Enable CI/CD for ML systems with modern orchestration tools
• Advocate for scalability, performance, and clean code in all deployed solutions

Interview Process:

Interview #1: Phone Screen with Talent Acquisition Team
Interview #2: Technical Interview – Round 1 with AI/ML Team (via MS Teams / F2F)
Interview #3: Technical Interview – Round 2 with AI/ML Team (via MS Teams / F2F)
Interview #4: Final Round with Hiring Manager and Cross-functional Stakeholders (via MS Teams / F2F

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 accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.