Optum Campus Drive 2026 Hiring Associate AI/ML Engineer

Optum Campus Drive 2026 Hiring Associate AI/ML Engineer

Optum Campus Drive 2026 brings an exciting career opportunity for fresh graduates and aspiring technology professionals interested in artificial intelligence and machine learning. Optum is hiring for the Associate AI/ML Engineer position, offering eligible candidates an opportunity to work with data-driven solutions, explore machine learning technologies, and contribute to innovative engineering projects. Interested applicants should check the official job notification for eligibility criteria, educational qualifications, programming skills, technical requirements, job responsibilities, work location, and selection process. Candidates with knowledge of Python, machine learning, artificial intelligence, data science, statistics, and problem-solving can explore this opportunity based on the specific role requirements. If you are searching for AI/ML engineering jobs and campus placement opportunities in 2026, visit the official Optum Careers portal for the latest vacancies and application details.

Job Details:

• Designation: Associate AI/ML Engineer
• Company: Optum
• Educational Qualification: B.E/B.Tech
• Experience Required: 0 – 3 Years
• Location: Hyderabad, India
• Compensation: Best in Industry

Job Description:

As an Associate AI/ML Engineer, you will join an innovative engineering team dedicated to transforming healthcare delivery through advanced artificial intelligence and machine learning solutions. In this role, you will contribute directly to designing, developing, and operationalizing generative AI, retrieval-augmented generation (RAG) systems, and agentic workflows that solve complex business and clinical challenges. You will collaborate with cross-functional software and data teams to build secure, scalable, and reliable production-grade AI applications using modern cloud services and enterprise data platforms.

Required Qualifications:

• 3+ years of software engineering experience, including hands-on experience building AI/GenAI or LLM-based applications (e.g., RAG systems, agentic workflows, or AI chatbots)
• Experience designing and building both batch and real-time streaming data pipelines using Spark, Scala, or Python
• Hands-on experience working with event-streaming or distributed messaging platforms (e.g., Apache Kafka, Azure Event Hubs, or Spark Structured Streaming)
• Experience building data pipelines within cloud data platforms such as Azure Databricks or Snowflake
• Practical experience integrating foundation models via commercial or open-source APIs (e.g., Azure OpenAI, OpenAI, Anthropic, Amazon Bedrock)
• Hands-on experience with at least one GenAI orchestration framework (e.g., LangChain, LangGraph, or Spring AI)
• Firm understanding of RAG components (chunking, embeddings, vector indexing, retrieval, prompt engineering) and agentic patterns (tool/function calling, memory, orchestration)
• Solid understanding of REST APIs, microservices architecture, Git, CI/CD pipelines, and Docker containerization
• Awareness of security, privacy, and responsible AI practices when building production systems

Preferred Qualifications:

• Relevant certifications in data engineering or cloud AI/ML (e.g., Databricks Certified Data Engineer, Azure AI Engineer Associate, Confluent Certified Developer for Apache Kafka)
• Experience modeling and serving streaming or batch datasets to PowerBI for operational and executive reporting
• Experience implementing LLM observability, evaluation, and guardrail frameworks (e.g., MLflow, Langfuse, or TruLens)
• Familiarity with data governance, schema registry, and data quality frameworks in streaming architectures
• Good understanding of analytics tools: Python, SQL, Databricks, Snowflake
• Good knowledge of Business intelligence tools like Tableau/Power BI, etc.
• Solid problem-solving skills
• Good knowledge around Predictive & Prescriptive Analytics techniques like Hypothesis testing, Probability, Supervised & Unsupervised Learnings
• Ability in slicing and dicing of data structures, Natural Language Processing and good to have fundamental understanding on Gen-AI & Large Language Models

Primary Responsibilities:

• Design and implement AI systems for conversational search in M&R Sales content
• Develop AIML based data ingestion quality gates based on pattern analysis
• Evaluate, debug, and improve conversational AI to ensure accuracy and efficiency
• Monitor and optimize system performance for latency, cost, and reliability
• Explore and apply reinforcement learning and self-improving techniques
• Collaborate and communicate effectively with cross-functional teams and stakeholders to deliver scalable solutions
• Ensure responsible and ethical AI practices throughout all stages of development
• Design, build, and deploy production-grade AI-powered solutions, including agentic workflows, RAG architectures, and conversational AI applications that solve complex enterprise challenges.
• Develop, optimize, and maintain scalable batch and real-time streaming data pipelines using Spark (including Spark Structured Streaming), Scala, and Python within Azure Databricks and Snowflake.
• Integrate event-streaming technologies (e.g., Apache Kafka, Azure Event Hubs) to process continuous, low-latency data feeds for real-time inference, dynamic context retrieval, and vector store updates
• Expose AI model outputs and streaming analytics via secure REST APIs and microservices, connecting data streams to downstream business platforms and interactive PowerBI dashboards
• Apply security best practices, data privacy standards, and responsible AI principles across all data processing and application workflows
• Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements.

Interested students can apply directly at 👉 Optum Campus Drive 2026

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