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Remote AI Engineer

Roles & Responsibilities

  • 3+ years of experience in AI Engineering, Machine Learning, or Software Engineering.
  • Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face.
  • Experience working with LLMs and AI platforms (OpenAI APIs, Anthropic, Gemini, or similar).
  • Experience deploying AI applications on cloud platforms (AWS, GCP, or Azure) and with APIs, backend systems, and scalable architectures.

Requirements:

  • Design, build, and deploy AI and machine learning solutions for real-world business applications.
  • Develop and maintain applications using Large Language Models (LLMs) such as GPT-based systems.
  • Build AI-powered automations, copilots, chatbots, and workflow systems.
  • Fine-tune, evaluate, and optimize machine learning models for performance and scalability.

Job description

About Huzzle

At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI.

Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team.

Role Type: Full-time

Engagement: Independent Contractor

Job Summary

As an AI Engineer, you will be responsible for developing and optimizing AI systems, integrating machine learning models into production environments, and building scalable AI-driven applications. You will contribute to everything from model experimentation to deployment and performance optimization.

Key Responsibilities

  • Design, build, and deploy AI and machine learning solutions for real-world business applications.
  • Develop and maintain applications using Large Language Models (LLMs) such as GPT-based systems.
  • Build AI-powered automations, copilots, chatbots, and workflow systems.
  • Fine-tune, evaluate, and optimize machine learning models for performance and scalability.
  • Integrate AI systems with APIs, databases, CRMs, and third-party platforms.
  • Collaborate with product and engineering teams to translate business requirements into AI-driven solutions.
  • Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems.
  • Monitor model performance, reliability, and cost efficiency in production environments.
  • Maintain documentation, testing procedures, and deployment workflows.
  • Stay updated on the latest AI trends, frameworks, and emerging technologies.

Requirements

  • 3+ years of experience in AI Engineering, Machine Learning, or Software Engineering.
  • Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face.
  • Experience working with LLMs, OpenAI APIs, Anthropic, Gemini, or similar AI platforms.
  • Familiarity with vector databases, embeddings, and RAG architectures.
  • Experience deploying AI applications using cloud platforms such as AWS, GCP, or Azure.
  • Strong understanding of APIs, backend systems, and scalable application architecture.
  • Experience with Docker, Git, CI/CD pipelines, and modern development practices.
  • Excellent problem-solving and analytical thinking skills.
  • Strong communication skills with the ability to work in remote, cross-functional teams.
  • Bonus: Experience building AI agents, automation systems, or voice AI applications.

Benefits

πŸ’° Competitive salary based on experience and location

🌎 Fully remote role with flexible work environment

πŸš€ Work on cutting-edge AI automation projects with real business impact

πŸ“ˆ Strong growth opportunity into senior AI / systems roles

🧠 Exposure to LLMs, prompt engineering, and scalable AI system design

🀝 Direct collaboration with a fast-moving, high-performance team

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