ML Engineer

Performacentric · United States · posted today ago

engineering python machine-learning remote jobs in united states

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About this role

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.

Responsibilities

AI 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 Qualifications

Technical 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.