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Remote Prompt Engineering Jobs in Indiana (NOW HIRING)

Performacentric

ML Engineer

Indianapolis, IN · On-site +1

Remote (Preferred U.S. Time Zones) Employment Type: Full-Time Company: Performacentric About ... Develop prompt engineering, retrieval, and agentic workflows. * Fine-tune and evaluate LLM ...

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Remote Prompt Engineering information

See Indiana salary details

$16

$31

$45

How much do remote prompt engineering jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for remote prompt engineering in Indiana is $31.46, according to ZipRecruiter salary data. Most workers in this role earn between $25.14 and $36.35 per hour, depending on experience, location, and employer.

How can I make 2000 a week working from home?

Remote prompt engineering is a freelance or contract role that can generate significant income if you have strong skills in AI, natural language processing, and prompt design. Earning $2000 weekly typically requires multiple clients, high-quality work, and efficient time management, often involving project-based tasks or retainer agreements. Building a portfolio and gaining experience with tools like GPT models can help increase earning potential.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

What is the difference between Remote Prompt Engineering vs Remote Data Annotation Specialist?

AspectRemote Prompt EngineeringRemote Data Annotation Specialist
Required CredentialsBasic understanding of AI, NLP, and scripting skillsAttention to detail, familiarity with annotation tools, no formal certifications required
Work EnvironmentCollaborative with AI/ML teams, remote setupIndependent annotation tasks, remote or on-site
Industry UsageAI development, NLP projects, machine learningData labeling for AI training datasets
Search & Comparison IntentUnderstanding roles in AI development, job requirementsData labeling jobs, annotation tasks, related roles

Remote Prompt Engineering involves designing and refining prompts for AI models, requiring some technical skills and collaboration with AI teams. In contrast, Remote Data Annotation Specialists focus on labeling data to train AI systems, emphasizing attention to detail. Both roles are essential in AI development but differ in skills and daily tasks.

What are some common challenges faced by remote prompt engineers, and how can they be addressed?

Remote prompt engineers often face challenges related to communication and collaboration, especially when working across time zones and with interdisciplinary teams. Staying updated on rapidly evolving AI technologies and understanding nuanced user requirements can also be demanding. To address these, prompt engineers can leverage collaborative tools, maintain clear documentation, and participate in regular team syncs. Building a habit of continuous learning and engaging in knowledge-sharing sessions helps keep skills relevant and fosters a sense of connection despite remote work.

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

To thrive as a Remote Prompt Engineer, you need a strong background in natural language processing, programming (often Python), and an understanding of AI/ML concepts, typically supported by a relevant degree or industry experience. Familiarity with large language models (like OpenAI's GPT), prompt optimization tools, and version control systems such as Git is common. Creativity, problem-solving, and strong written communication are vital soft skills for designing effective prompts and collaborating remotely. These skills ensure the development of high-performing AI solutions and seamless teamwork in distributed environments.

Are prompt engineers still in demand?

Prompt engineering is a growing field as organizations seek to optimize AI language models for various applications. Demand for prompt engineers is increasing, especially for roles involving natural language processing, AI model tuning, and familiarity with tools like GPT and other large language models.

How to make $1000 a week remote?

Remote prompt engineering involves creating and refining prompts for AI models, and experienced professionals can earn around $20 to $50 per hour. To make $1000 weekly, one would need to work approximately 20 to 50 hours at this rate, often requiring strong language skills, familiarity with AI tools, and consistent project availability. Building a portfolio and gaining certifications can help increase earning potential in this field.

What is remote prompt engineering?

Remote prompt engineering is the practice of designing and refining prompts for AI language models, such as ChatGPT, while working from a remote location. Prompt engineers craft instructions or questions to optimize the model’s responses for specific tasks or applications. This role typically involves understanding both the capabilities and limitations of AI systems, as well as the needs of end users or clients. Remote prompt engineers collaborate online with teams and may work for tech companies, research organizations, or as independent contractors.
What are the most commonly searched types of Prompt Engineering jobs in Indiana? The most popular types of Prompt Engineering jobs in Indiana are:
What are popular job titles related to Remote Prompt Engineering jobs in Indiana? For Remote Prompt Engineering jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Remote Prompt Engineering jobs in Indiana look for? The top searched job categories for Remote Prompt Engineering jobs in Indiana are:
What cities in Indiana are hiring for Remote Prompt Engineering jobs? Cities in Indiana with the most Remote Prompt Engineering job openings:
Remote Prompt Engineering jobs near you

ML Engineer

Performacentric

Indianapolis, IN • On-site, Remote

Full-time

Posted 12 days ago

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.