AI/ML Engineer / Generative AI Engineer

Talent Software Services, Inc.

  • Indianapolis, IN
  • 9 days ago
  • $56.81 Per Hour

Highlights

Design, engineer, and implement enterprise-scale AI/ML and Generative AI solutions for clinical data workflows. Strong experience with AWS, Databricks, Python, PySpark, and DevOps technologies.

Numbers & Facts

LocationIndianapolis, IN
Salary$56.81 Per Hour

Description

Job Details

  • Job Title: AI/ML Engineer / Generative AI Engineer
  • Location: Indianapolis, IN
  • Duration: 6 months
  • GBaMS ReqID: 10937381
  • Essential / Digital Skill: Artificial Intelligence (AI)
  • Experience Required: 4–6 years

Role Summary

  • Design, engineer, and implement enterprise-scale AI/ML and Generative AI solutions for clinical data workflows.
  • Deliver secure and scalable AI architectures independently.
  • Maintain accountability for project delivery and technical excellence.
  • Develop solutions supporting clinical data workflows and enterprise AI initiatives.

Key Responsibilities

  • Conceive, design, and implement AI solutions.
  • Analyze business and technical workflows and develop innovative technical approaches.
  • Design secure and scalable architectures for:
    • AI/ML
    • Generative AI
    • Agentic AI solutions
  • Design and implement emerging AI technologies, including:
    • Retrieval-Augmented Generation (RAG)
    • Agentic workflows
    • Agent-to-agent communication
  • Build and deploy predictive analytics and Generative AI solutions into production.
  • Develop robust:
    • Data pipelines
    • Model pipelines
    • APIs
    • Integration layers
  • Establish and implement AI/MLOps best practices.
  • Implement:
    • CI/CD pipelines
    • Monitoring
    • Observability
  • Own project scope and delivery accountability.
  • Ensure AI solutions meet enterprise security, scalability, and reliability requirements.

Required Qualifications

  • Bachelor’s degree in:
    • Computer Science
    • Engineering
    • Mathematics
    • Statistics
    • Related field
  • Equivalent professional experience may be considered.
  • 5+ years of software, data, or ML engineering experience.
  • 3+ years of experience deploying ML solutions into production.
  • Strong experience with AWS, Databricks, Python, PySpark, and DevOps technologies.

AWS Technologies

  • Amazon SageMaker
  • Amazon EC2
  • Amazon S3
  • AWS Lambda
  • Amazon RDS
  • AWS Glue
  • Amazon Athena
  • Amazon DynamoDB
  • PostgreSQL

Databricks Technologies

  • Databricks Platform
  • Delta Lake
  • Apache Spark
  • MLflow
  • Databricks SQL

Programming & Data

  • Python
  • PySpark
  • SQL
  • Apache Spark

DevOps & Infrastructure

  • Git
  • CI/CD
  • Docker
  • Kubernetes
  • Infrastructure as Code (IaC)
  • Terraform
  • CloudFormation

AI & Data Technologies

  • Generative AI frameworks
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Agentic AI
  • Agent-to-agent communication
  • Vector Databases
  • Predictive Analytics
  • Machine Learning
  • AI/MLOps

Key Skills / Keywords

  • Artificial Intelligence (AI)
  • Machine Learning
  • Generative AI
  • Agentic AI
  • LLMs
  • RAG
  • Vector Databases
  • AWS
  • SageMaker
  • Databricks
  • Delta Lake
  • Spark
  • MLflow
  • Python
  • PySpark
  • SQL
  • CI/CD
  • Docker
  • Kubernetes
  • Terraform
  • CloudFormation
  • MLOps
  • Clinical Data Workflows
  • Predictive Analytics

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