Hyderabad, Telangana, India
Actively hiring, first seen by us todayDesign and deploy production AI systems such as RAG, agentic workflows and conversational AI
Build batch and real-time streaming data pipelines using Spark, Scala and Python
Integrate event streaming such as Kafka or Event Hubs for real-time inference and vector store updates
Expose AI outputs through secure REST APIs and microservices, and feed PowerBI dashboards
Evaluate, debug and improve conversational AI for accuracy and efficiency
Design, build, and deploy production-grade AI-powered solutions, including agentic workflows, RAG architectures, and conversational AI applications
Develop, optimize, and maintain scalable batch and real-time streaming data pipelines using Spark
Integrate event-streaming technologies (e.g., Apache Kafka, Azure Event Hubs) to process continuous, low-latency data feeds
Expose AI model outputs and streaming analytics via secure REST APIs and microservices
Evaluate, debug, and improve conversational AI to ensure accuracy and efficiency
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)
Experience modeling and serving streaming or batch datasets to PowerBI for operational and executive reporting
Good knowledge around Predictive & Prescriptive Analytics techniques like Hypothesis testing, Probability, Supervised & Unsupervised Learnings
Experience implementing LLM observability, evaluation, and guardrail frameworks (e.g., MLflow, Langfuse, or TruLens)
Ability in slicing and dicing of data structures, Natural Language Processing and good to have fundamental understanding on Gen-AI & Large Language Models
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Early. Similar jobs usually come down between day 7 and day 72.
At UnitedHealth Group, jobs usually come down by about day 12.
From 4,777 similar postings that came down, and 880 of UnitedHealth Group’s. Coming down is not always a hire.
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Open jobs by the week we first saw them, last 12 weeks.
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- 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
- 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)
- 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.
- 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
- 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
- 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)
- 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)
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
- 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
- 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
- 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
- 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)
- Good understanding of analytics tools: Python, SQL, Databricks, Snowflake - Good knowledge of Business intelligence tools like Tableau/Power BI, etc. - Solid problem-solving skills
Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.
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Yes. We’ve followed 8 other Associate AI/ML Engineer jobs there since May 2026. 5 came down, usually after about 7 days. 3 are still up.
If this one keeps the same pace, it may come down around November 16.
Large employers often post one title for several teams, so these can be separate openings.
New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
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.
Primary Responsibilities:
Required Qualifications:
Preferred Qualifications:
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
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Hyderabad, Telangana, India
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