ML Engineer With Heavy Azure-Princeton, NJ (Fully Onsite)-C2C- CH

Role: ML Engineer With Heavy Azure

Locations: Princeton, NJ (Fully Onsite)

Duration: 12+ Months Contract

Note: Candidate needs to be in the office 5 Days every week. Local or candidates from adjacent states only.

Job Description:

• We are seeking a candidate with 8+ years of experience in Data Engineering and Machine Learning, with strong expertise in Azure Data Platform and hands-on experience in LLM-based solutions and Retrieval-Augmented Generation (RAG) architectures.
• The ideal candidate will design, implement, and optimize data and AI solutions leveraging Microsoft Azure and modern AI frameworks.

Responsibilities:

• Design and develop data ingestion pipelines from source systems using Azure Databricks and Azure Data Factory into the Azure Analytics Platform.
• Build and optimize ETL/ELT pipelines for structured and unstructured data.
• Develop and deploy LLM-powered applications, including RAG-based solutions for enterprise use cases.
• Implement vector databases and embedding-based retrieval systems to support RAG workflows.
• Integrate LLMs with Azure services (e.g., Azure OpenAI, Cognitive Search) for intelligent data processing and insights.
• Apply Python, PySpark, and modern ML frameworks to build scalable AI solutions.
• Provide technical design and coding guidance to the team to achieve project deliverables.
• Ensure CI/CD integration using Azure DevOps for ML and data pipelines.
• Collaborate with business stakeholders to gather requirements and translate them into technical solutions.
• Stay current with AI/ML trends, including Generative AI, LLM fine-tuning, and prompt engineering.

Skills & Expertise:

• Azure Data Factory, Azure Databricks, Azure DevOps, Azure Storage/Data Lake
• ETL & ELT, Data Warehousing, SQL, Relational Databases
• Python, PySpark, and ML frameworks (e.g., Hugging Face, LangChain)
• LLM development and deployment (Azure OpenAI, or similar)
• RAG architecture design, Vector Databases (e.g., Pinecone, Weaviate, FAISS)
• Prompt Engineering, LLM Fine-tuning, and Model Evaluation
• Experience with Cloud Platforms (Azure is a must)

Preferred Qualifications:

• Experience with MLOps for LLMs, including model lifecycle management and monitoring.
• Knowledge of semantic search, embedding optimization, and knowledge graph integration.
• Familiarity with distributed systems and scalable AI architectures.
• Understanding of data governance, security, and compliance in AI/ML solutions.
• Strong problem-solving skills and ability to architect end-to-end AI solutions.

Thanks

Anil Singh

Technical Recruiter | Empower Professionals

anil@empowerprofessionals.com |Official Phone: x 381

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Fax: | 100 Franklin Square Drive Suite 104 | Somerset, NJ 08873

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