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Power Gpu Jobs in Indiana (NOW HIRING)

Eightelevengroup

GS - Data Science Pod

Indianapolis, IN · On-site

$171.92/hr

... power digital health studies and clinical trials. As a Data Engineer, you will play a pivotal role ... modern compute/GPU approaches for generating insights at scale. * Contribute to internal ...

New

Brooksource

GS - Data Science Pod

Indianapolis, IN · On-site

$55 - $75/hr

... power digital health studies and clinical trials. As a Data Engineer, you will play a pivotal role ... modern compute/GPU approaches for generating insights at scale. * Contribute to internal ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

Why This Role Matters: We're building AI&ML-powered products that will transform how Group 1001 ... endpoints, and efficient GPU utilization * Integrate ML infrastructure with our Dagster ...

All JobsPower Gpu JobsPower Gpu Jobs in Indiana

Power Gpu information

See Indiana salary details

$12

$23

$44

How much do power gpu jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for power gpu in Indiana is $23.32, according to ZipRecruiter salary data. Most workers in this role earn between $17.16 and $26.97 per hour, depending on experience, location, and employer.

What is a Power GPU?

Power GPU is a company that specializes in building custom gaming and workstation PCs tailored to individual needs and preferences. They help customers choose the right components for optimal performance, assemble the systems, and provide support after the purchase. Their team has expertise in balancing performance, aesthetics, and budget, making them a popular choice among gamers, content creators, and professionals seeking high-performance computers.

What are the key skills and qualifications needed to thrive as a Power GPU technician?

To excel as a Power GPU Technician, you need strong knowledge of computer hardware assembly, troubleshooting, and maintenance, typically backed by experience or relevant certifications such as CompTIA A+. Familiarity with diagnostic tools, GPU benchmarking software, and system monitoring utilities is essential. Attention to detail, problem-solving skills, and effective communication help you deliver high-quality builds and support to clients. These skills ensure reliable system performance, customer satisfaction, and the ability to resolve complex technical issues efficiently.

What are some common challenges faced by Power GPU engineers when optimizing performance in modern hardware?

GPU Power Engineers often contend with balancing high computational performance and stringent power consumption targets, especially as hardware becomes more complex. They must analyze power usage at both the architectural and circuit levels, implement power-saving features, and ensure thermal constraints are met without sacrificing speed. Collaboration with cross-functional teams, such as hardware designers and software developers, is key to identifying and addressing power bottlenecks. Staying current with evolving technologies and industry standards is also essential for success in this dynamic role.

What is the difference between Power Gpu vs Graphics Processing Unit (GPU)?

AspectPower GpuGraphics Processing Unit (GPU)
Primary FunctionSpecialized high-performance computing for AI, deep learning, and data centersRendering graphics and visual data for gaming, design, and multimedia
Required CredentialsAdvanced certifications in AI, hardware engineering, or data center managementBasic to advanced knowledge of graphics architecture, often with related certifications
Work EnvironmentData centers, AI research labs, enterprise environmentsDesign studios, gaming companies, multimedia production
Industry UsageAI, machine learning, data processing industriesGaming, entertainment, digital content creation

Power Gpu and Graphics Processing Units (GPU) are related but serve different purposes. Power Gpu focuses on high-performance computing for AI and data centers, while GPUs are primarily used for rendering graphics in gaming and multimedia. Understanding these differences helps professionals choose the right role based on their skills and industry needs.

What are popular job titles related to Power Gpu jobs in Indiana?

For Power Gpu jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Power Gpu jobs in Indiana look for?

The top searched job categories for Power Gpu jobs in Indiana are:

What cities in Indiana are hiring for Power Gpu jobs?

Cities in Indiana with the most Power Gpu job openings:

Power Gpu jobs near you
Infographic showing various Power Gpu job openings in Indiana as of June 2026, with employment types broken down into 75% Full Time, 14% Part Time, and 11% Contract. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $48,508 per year, or $23.3 per hour.

GS - Data Science Pod

Eightelevengroup

Indianapolis, IN • On-site

$171.92/hr

Other

Posted 3 days ago

New

Job description

Data Engineer, Data and Platform Engineering

Hybrid Role (downtown Indy 3x / week)

Compensation: $60 - $75

ABOUT THE ROLE

Join a global healthcare leader dedicated to uniting caring with discovery to make life better for people around the world. As part of the Digital Health organization, the Data and Platform Engineering team transforms wearable and sensor data into trusted, analysis-ready datasets that power digital health studies and clinical trials. As a Data Engineer, you will play a pivotal role in building and maintaining the pipelines, automation, and quality systems that connect digital health technologies (DHT) to scientists and clinical teams, directly impacting how disease is measured and new medicines are evaluated. You will collaborate with study teams from the earliest stages of study design, ensure the quality and traceability of data, and support the integration of AI and advanced analytics into the digital health platform. This is an opportunity to contribute to research and innovation in digital health technologies, with a focus on automation, data integrity, and scalable infrastructure.

WHAT YOU'LL DO
  • Support early-stage design of digital health technology (DHT) studies by collaborating with study teams to understand study objectives, physiological signals of interest, and practical data collection requirements.
  • Build, operate, and maintain scalable data pipelines for wearable and sensor data, ensuring reliable data flow from collection to analysis-ready datasets.
  • Monitor and track the flow of DHT and clinical trial data through pipelines, identifying and addressing issues such as device malfunctions, wear compliance, and emerging data quality problems.
  • Develop and maintain automated data quality check systems, performing root-cause analysis and ensuring data traceability, reproducibility, and compliance with regulatory standards.
  • Manage data storage and organization for raw and processed data, maintaining secure, efficient, and well-documented access across teams and replicating data as needed.
  • Serve as a primary developer for pipeline code, including data movement, processing, aggregation, quality control, and integration of AI capabilities.
  • Build and maintain internal platforms and APIs to expose curated pipeline data to AI tools and assistants used across the team.
  • Configure and manage compute infrastructure that supports AI-driven research, model development, and large-scale data processing.
  • Participate in model or algorithm development activities, including work on novel wearables, sleep detection, 3D environment reconstruction, and modern compute/GPU approaches for generating insights at scale.
  • Contribute to internal discussions and strategy regarding the use of digital health technologies and wearables in both in-clinic and at-home research settings.
  • Stay current with relevant academic research and contribute to publications produced by the team.
  • Present technical work to internal and external audiences, ensuring clear, audience-appropriate storytelling and effective communication.
WHAT YOU BRING
  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field (Master's or PhD considered); 3-5 years of professional data engineering experience.
  • Strong programming skills in Python and SQL, with hands-on experience building and maintaining production data pipelines (ETL/ELT).
  • Experience with cloud computing platforms (e.g., Azure, AWS, or GCP) and modern data engineering tools.
  • Working knowledge of relational and non-relational database technologies and data modeling practices.
  • Demonstrated ability to identify data quality issues and build automated checks to catch and resolve them.
  • Experience working with wearable sensor data, time-series data, or other high-frequency data streams.
  • Experience building, refining, or productionizing machine learning models, especially for classification or signal/time-series data (e.g., activity or sleep detection).
  • Experience integrating AI or large language models (LLMs) into data platforms or applications.
  • Experience in a regulated industry (healthcare, life sciences, or clinical research) is a plus.
  • Strong written and verbal communication skills, with the ability to present technical work to both technical and non-technical audiences.
  • Collaborative, growth-oriented mindset; willingness to learn new tools, languages, and domain knowledge as needed.

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