AI Engineer - Remote

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.

We are looking for a highly skilled AI Engineer to design, build, and deploy AI-driven applications and machine learning solutions. You’ll work closely with product, engineering, and data teams to create intelligent systems that improve automation, customer engagement, and operational efficiency.

This role is ideal for someone passionate about artificial intelligence, large language models (LLMs), machine learning infrastructure, and production-grade AI systems.

• →Design, develop, and deploy AI and machine learning models for real-world applications.
• →Build and optimize AI-powered tools using technologies such as OpenAI, Claude, Gemini, or open-source LLMs.
• →Develop scalable APIs and backend services for AI applications.
• →Fine-tune machine learning models and improve model performance.
• →Work with structured and unstructured datasets for training and inference.
• →Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines.
• →Integrate AI solutions into web platforms, CRMs, and business systems.
• →Monitor AI model performance, reliability, and scalability in production.
• →Collaborate with cross-functional teams to define AI product requirements and technical roadmaps.
• →Stay updated on emerging AI technologies, frameworks, and best practices.

• 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, generative AI tools, and prompt engineering.
• Familiarity with vector databases, embeddings, and RAG architectures.
• Knowledge of cloud platforms such as AWS, GCP, or Azure.
• Experience building REST APIs and scalable backend systems.
• Understanding of MLOps, model deployment, and monitoring workflows.
• Strong problem-solving and analytical thinking skills.
• Excellent communication and collaboration abilities.
• Experience working in remote or distributed teams is a plus.