AI/ML Engineer(Multi-Level)

Role & responsibilities

• Contribute to experimentation with novel ML and Generative AI architectures 
• Create and maintain embedding models (domain-specific embeddings, document/text embeddings) 
• Support Retrieval Augmented Generation (RAG) solutions, including semantic search, vector databases, and LLM integration 
• Help design and implement AI powered enterprise applications 
• Analyze large datasets to identify trends, patterns, and actionable insights 
• Partner with AI/ML Engineers and Leads to enhance existing models and improve model accuracy and performance 
• Optimize AI pipelines for scalability, performance, reliability, and cost efficiency 
• Integrate AI/ML solutions into enterprise systems by partnering closely with data engineering, product, and platform teams 
• Collaborate effectively with cross-functional teams and stakeholders, communicating complex technical concepts clearly 
• Contribute to skill development for engineers and interns in AI/LLM techniques 
• Comply with company policies, procedures, and directives
• 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

Preferred candidate profile

• Graduate degree or equivalent experience
• Bachelors/Master’s in CS, Engineering, Mathematics/Statistics, or related 
• 4+ years of relevant experience, including solid ML model development 
• Hands-on expertise in Databricks, Spark, Python, Scala, SQL 
• LLM & GenAI Skills: 
• Creating custom embedding models 
• Building RAG pipelines 
• Vector DBs & semantic search 
• Using LangChain for agentic workflows (tools, agents, memory) 
• Experience with OpenAI/Azure OpenAI APIs 
• Experience with Azure cloud for compute, security, and resource management 
• CI/CD familiarity using Git, GitHub Actions/Jenkins, Terraform 
• Solid ability to build ML models end to end (data prep feature creation training evaluation) 
• Proven excellent communication and partnership skills