AI Engineer (Remote) - Part Time / Freelance

We are looking for talented and motivated AI Engineers to join our team and help design, build, and deploy intelligent AI-powered solutions.

Youll work across machine learning, generative AI, LLMs, data pipelines, and production AI systems, turning complex business problems into scalable and reliable products.

Key Responsibilities

• Design, develop, and deploy AI/ML models and applications.
• Build and integrate LLM and generative AI solutions.
• Develop AI agents, RAG pipelines, prompt workflows, and evaluation systems.
• Work with structured and unstructured data to develop intelligent solutions.
• Integrate AI models with existing products, APIs, and business systems.
• Optimise models and applications for performance, scalability, cost, and reliability.
• Build and maintain production-grade ML/AI pipelines.
• Monitor AI systems and continuously improve model quality.
• Collaborate with software engineers, data scientists, product managers, and business stakeholders.
• Stay up to date with the latest developments in AI, machine learning, and generative AI.

Required Skills & Experience

• Strong Python programming skills.
• Experience with machine learning and AI frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Hands-on experience with LLMs and Generative AI.
• Experience working with APIs and cloud-based AI services.
• Understanding of RAG, embeddings, vector databases, and prompt engineering.
• Experience with databases and data processing.
• Familiarity with Git, CI/CD, Docker, and software engineering best practices.
• Strong problem-solving and analytical skills.
• Ability to translate business requirements into practical AI solutions.

Nice to Have

• Experience building AI agents or multi-agent systems.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, or pgvector.
• Knowledge of MLOps and model monitoring.
• Experience deploying AI applications at scale.
• Knowledge of NLP, computer vision, or reinforcement learning.
• Experience with Kubernetes and infrastructure-as-code.