2

Remote Ai Infrastructure Engineer Jobs in Indiana

ML Engineer

Indianapolis, IN ยท On-site +1

Machine Learning Engineer (Llama AI Platform) Location: Remote (Preferred U.S. Time Zones ... Data & Infrastructure * Build and maintain vector database integrations. * Develop data ingestion ...

New

Senior AI Engineer

South Bend, IN ยท On-site +1

$102K - $140K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... Troubleshoot complex pipeline failures, infrastructure errors, and distributed system bottlenecks

Senior AI Engineer

Indianapolis, IN ยท On-site +1

$99K - $137K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... Troubleshoot complex pipeline failures, infrastructure errors, and distributed system bottlenecks

AI Automation Engineer -Remote

Hammond, IN ยท On-site +1

$202K - $234K/yr

About the Team and Role: We're hiring our first AI Automation Engineer to lead how we apply AI ... remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are ...

AI Automation Engineer -Remote

South Bend, IN ยท On-site +1

$202K - $234K/yr

About the Team and Role: We're hiring our first AI Automation Engineer to lead how we apply AI ... remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are ...

AI Automation Engineer -Remote

Fort Wayne, IN ยท On-site +1

$202K - $234K/yr

About the Team and Role: We're hiring our first AI Automation Engineer to lead how we apply AI ... remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are ...

next page

Showing results 1-20

Remote Ai Infrastructure Engineer information

What are the key skills and qualifications needed to thrive as a Remote AI Infrastructure Engineer, and why are they important?

To thrive as a Remote AI Infrastructure Engineer, you need expertise in cloud computing, distributed systems, and software engineering, often supported by a degree in computer science or a related field. Familiarity with tools like Kubernetes, Docker, Terraform, and cloud platforms such as AWS, Azure, or GCP is typically required, along with knowledge of CI/CD pipelines and AI/ML frameworks. Strong problem-solving skills, self-motivation, and effective remote communication are essential soft skills for success in this role. These skills ensure robust, scalable AI infrastructure that supports rapid innovation and seamless collaboration across distributed teams.

What is a Remote AI Infrastructure Engineer?

A Remote AI Infrastructure Engineer is a professional who designs, builds, and maintains the systems and tools necessary to support artificial intelligence (AI) projects, all while working remotely. Their responsibilities often include developing and optimizing cloud or on-premise infrastructure, ensuring scalability, managing data pipelines, and supporting machine learning workflows. They work closely with data scientists and software engineers to ensure AI models can be efficiently trained, deployed, and monitored in production environments. The remote aspect allows them to perform these tasks from anywhere, using collaboration tools and cloud platforms.

What are some common challenges faced by Remote AI Infrastructure Engineers, and how can they be addressed?

Remote AI Infrastructure Engineers often encounter challenges such as managing distributed systems, ensuring robust data pipelines, and maintaining high system reliability across different time zones. Collaboration with cross-functional teams can require clear communication and effective use of remote tools. To address these challenges, it's important to establish strong documentation practices, schedule regular check-ins, and utilize automated monitoring and deployment solutions. Staying proactive and adaptable helps ensure seamless infrastructure performance and team alignment.
What are the most commonly searched types of Ai Infrastructure Engineer jobs in Indiana? The most popular types of Ai Infrastructure Engineer jobs in Indiana are:
What are popular job titles related to Remote Ai Infrastructure Engineer jobs in Indiana? For Remote Ai Infrastructure Engineer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Remote Ai Infrastructure Engineer jobs in Indiana look for? The top searched job categories for Remote Ai Infrastructure Engineer jobs in Indiana are:
What cities in Indiana are hiring for Remote Ai Infrastructure Engineer jobs? Cities in Indiana with the most Remote Ai Infrastructure Engineer job openings:

ML Engineer

Performacentric

Indianapolis, IN โ€ข On-site, Remote

Full-time

Posted yesterday


Job description

Machine Learning Engineer (Llama AI Platform)

Location: Remote (Preferred U.S. Time Zones)
Employment Type: Full-Time
Company: Performacentric

About Performacentric

Performacentric helps small and mid-market organizations improve profitability, efficiency, visibility, employee performance, customer satisfaction, and supplier performance through custom AI agents, intelligent automation, and connected business systems.

We are building a next-generation AI platform powered by open-source large language models, agentic workflows, and business process automation. We are seeking a Machine Learning Engineer to help design, deploy, and optimize AI solutions built on Llama models and modern Python-based application architectures.

Position Summary

Performacentric is seeking a Machine Learning Engineer with hands-on experience developing and deploying AI applications using Llama 3 8B, Python, and FastAPI. This role will be responsible for building production-grade AI services, optimizing model performance, developing APIs, integrating business systems, and supporting the evolution of Performacentric's AI agent platform.

The ideal candidate combines strong software engineering skills with practical machine learning experience and enjoys working in a fast-paced startup environment where they can directly influence product direction and technical architecture.

ResponsibilitiesAI Model Development & Optimization
  • Deploy, configure, and optimize Llama 3 8B models for production use.
  • Develop prompt engineering, retrieval, and agentic workflows.
  • Fine-tune and evaluate LLM performance for business use cases.
  • Implement Retrieval-Augmented Generation (RAG) architectures.
  • Optimize inference performance, latency, and infrastructure utilization.
  • Monitor model quality and continuously improve response accuracy.
Application Development
  • Build scalable AI applications using Python and FastAPI.
  • Design and maintain RESTful APIs for AI services.
  • Develop backend services supporting AI agents and copilots.
  • Integrate AI solutions with CRM, ERP, communication, and business systems.
  • Implement authentication, authorization, and API security controls.
  • Write clean, maintainable, and well-documented code.
Data & Infrastructure
  • Build and maintain vector database integrations.
  • Develop data ingestion and preprocessing pipelines.
  • Support deployment of AI workloads in cloud and self-hosted environments.
  • Collaborate on model serving, monitoring, logging, and observability.
  • Assist with infrastructure automation and CI/CD processes.
Collaboration
  • Work closely with product, engineering, and leadership teams.
  • Participate in architecture discussions and technical planning.
  • Contribute to AI solution design for client implementations.
  • Mentor junior developers and share best practices.
Required QualificationsTechnical Skills
  • 3+ years of professional software engineering experience.
  • Strong proficiency in Python.
  • Experience building APIs with FastAPI.
  • Experience deploying and working with Llama 3 8B or similar open-source LLMs.
  • Understanding of prompt engineering and LLM optimization techniques.
  • Experience consuming and developing REST APIs.
  • Strong understanding of Git-based development workflows.
  • Familiarity with Linux environments and command-line tools.
  • Experience troubleshooting and optimizing production applications.
Machine Learning Knowledge
  • Understanding of machine learning fundamentals.
  • Experience evaluating AI model performance.
  • Familiarity with embeddings, vector search, and RAG architectures.
  • Knowledge of model inference optimization techniques.
  • Experience working with structured and unstructured datasets.
Preferred Qualifications

Preference will be given to candidates with experience in one or more of the following:

  • Fine-tuning open-source LLMs.
  • ML Engineering and MLOps practices.
  • LangChain, LlamaIndex, Haystack, or similar frameworks.
  • PostgreSQL database administration and optimization.
  • Vector databases such as pgvector, Chroma, Pinecone, Weaviate, or Qdrant.
  • Docker and containerized deployments.
  • Kubernetes orchestration.
  • Azure AI infrastructure and GPU environments.
  • CI/CD pipelines and DevOps automation.
  • Multi-agent AI architectures.
  • Knowledge graph implementations.
  • Business intelligence and analytics platforms.
Success Metrics

Within the first 12 months, the successful candidate will help:

  • Deploy and optimize production AI workloads.
  • Improve AI response quality and accuracy.
  • Reduce inference latency and infrastructure costs.
  • Expand Performacentric's AI agent platform capabilities.
  • Deliver reliable AI integrations for customer environments.
  • Contribute to the development of new AI-powered products and services.
What We Offer
  • Opportunity to work on cutting-edge AI and agentic technologies.
  • Direct influence on product architecture and technical strategy.
  • Remote-first work environment.
  • Competitive compensation based on experience.
  • Professional growth opportunities in one of the fastest-growing areas of software development.
  • Ability to help shape the future of AI-powered business transformation.
How to Apply

Interested candidates should submit:

  • Resume/CV
  • Brief cover letter
  • GitHub profile (if available)
  • Portfolio of AI, machine learning, or software development projects
  • Examples of LLM, FastAPI, or AI agent implementations (preferred)

Join Performacentric and help build the next generation of AI agents that transform how businesses operate, make decisions, and grow.