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Aws Sagemaker Jobs in Indiana (NOW HIRING)

NEOGOV

Solution Architect

Indianapolis, IN · On-site

$55.25 - $72.75/hr

... AWS SageMaker, Azure ML, Google Vertex AI) • Knowledge of prompt engineering and fine-tuning large language models (LLMs) • Strong communication and presentation skills • Ability to explain ...

Deloitte

Cyber - AWS Cloud Security - Manager

Indianapolis, IN · On-site

$106K - $143K/yr

Experience securing machine learning, generative AI, or agentic AI workloads and pipelines on AWS, including Amazon Bedrock, Amazon SageMaker, or autonomous agent frameworks * Experience with AI/ML ...

Jj

Staff AI/ML Software Engr, Navigation

Warsaw, IN · On-site

Demonstratable expertise in ML model training/optimization, local/cloud (AWS Sagemaker, Azure Studio) * Experience developing AI systems in regulated environments (e.g., SaMD), such as surgical ...

Align Technology, Inc.

Strong proficiency in Python, and C#; solid grounding in systems design and distributed systems; solid understanding of AWS services (SageMaker, EC2, Lambda, S3, CloudWatch, RDS); experience with ...

New

CSAA

Provide technical leadership for AI/ML platforms including Palantir, AWS Bedrock, Amazon SageMaker, and related cloud-native technologies. * Ensure platform reliability, scalability, performance ...

All JobsAws Sagemaker JobsAws Sagemaker Jobs in Indiana

Aws Sagemaker information

See Indiana salary details

$10

$51

$73

How much do aws sagemaker jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for aws sagemaker in Indiana is $51.43, according to ZipRecruiter salary data. Most workers in this role earn between $36.83 and $61.30 per hour, depending on experience, location, and employer.

What is an AWS SageMaker?

An AWS SageMaker job typically refers to a role focused on building, training, and deploying machine learning models using Amazon SageMaker. Professionals in this role work with data preprocessing, model optimization, and cloud-based machine learning workflows. Responsibilities may include automating ML pipelines, monitoring performance, and integrating SageMaker with other AWS services. Knowledge of Python, TensorFlow, PyTorch, and AWS services is often required.

What does an AWS SageMaker do?

Day-to-day responsibilities for AWS SageMaker professionals typically include building, training, and deploying machine learning models using the SageMaker platform, preprocessing data, and monitoring the performance of deployed models. You'll often collaborate with data engineers, software developers, and business stakeholders to understand project requirements and deliver solutions that meet business objectives. Routine tasks may also involve tuning model hyperparameters, optimizing resource usage, and ensuring data security and compliance within AWS environments. This hands-on, collaborative workflow provides the opportunity to directly impact business outcomes while continuously developing your technical expertise.

What are the key skills and qualifications needed for an AWS SageMaker?

To excel in an AWS SageMaker-focused role, you need strong expertise in machine learning, data science, and cloud computing, often supported by a degree in computer science or a related field. Experience with AWS SageMaker, other AWS services (like S3 and Lambda), and certifications such as AWS Certified Machine Learning – Specialty are highly valued. Strong analytical thinking, problem-solving abilities, and effective communication skills help set candidates apart. Mastery of these areas ensures successful design, deployment, and management of scalable AI/ML solutions in dynamic business environments.

What are popular job titles related to Aws Sagemaker jobs in Indiana?

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Aws Sagemaker jobs near you
Infographic showing various Aws Sagemaker job openings in Indiana as of August 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution, with an average salary of $106,977 per year, or $51.4 per hour.

Generative AI Engineer

Indianapolis, IN • On-site

Prophecy Technologies
Professional, Scientific, and Technical Services • 11 - 50 employees
Learn more about Prophecy Technologiesexternal

Full-time

Posted 14 days ago

Job description

Role Overview:
Design, engineer, and implement enterprise-scale AI/ML and generative AI solutions for clinical data workflows. This role requires delivering secure, scalable architectures independently while maintaining accountability for project delivery and technical excellence.
Key Responsibilities:
  • Conceive, design, and implement AI solutions; analyze workflows and devise innovative technical approaches.
  • Design secure, scalable architectures for AI/ML, generative AI, and agentic solutions.
  • Design and implement emerging AI technologies such as RAG, agentic workflows, and agent-to-agent communication.
  • Build and deploy predictive analytics and generative AI solutions to production environments.
  • Develop robust data/model pipelines, APIs, and integration layers; establish AI/MLOps best practices.
  • Implement CI/CD, monitoring, and observability for AI/ML systems.
  • Own project scope and delivery accountability.

Required Skills:
  • Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda, RDS, Glue, Athena, DynamoDB, Postgres), Databricks (Platform, Delta Lake, Spark, MLflow, SQL).
  • Programming Languages & ML: Python, PySpark, SQL.
  • DevOps & Infrastructure: Git, CI/CD, Docker, Kubernetes, IaC (Terraform/CloudFormation).
  • AI/Data Technologies: Generative AI frameworks, Large Language Models (LLMs), vector databases, Apache Spark.

Qualifications:
  • Bachelor's degree (BS) in Computer Science, Engineering, Mathematics, Statistics or equivalent professional experience.
  • 5+ years of experience in software, data, or ML engineering.
  • 3+ years of experience deploying ML solutions in production environments.

Preferred Skills:
  • Digital Artificial Intelligence (AI) expertise.

Apply