AI Engineer

About the Role

We’re looking for a skilled AI Engineer to help us fine-tune, deploy, and maintain private AI models tailored to our business needs. You’ll be working with leading foundation models and custom datasets to deliver scalable, secure, and high-performing AI solutions—without reinventing the wheel.

🧠 Model Fine-Tuning & Adaptation

• Fine-tune pre-trained private AI models (e.g. LLMs, vision models) for specific business use cases.
• Host and manage local LLMs and app hosting
• Work with proprietary or internal datasets to adapt models for high relevance and accuracy.
• Evaluate model performance and improve outputs through prompt engineering or targeted retraining.

🧹 Data Preparation

• Collect, clean, and prepare datasets for training, tuning, and evaluation.
• Collaborate with data teams to ensure high-quality inputs and labeling consistency.

⚙️ Deployment & Operations

• Deploy models in secure, scalable production environments using Docker, Kubernetes, Linux and cloud infrastructure (AWS, GCP, or Azure).
• Monitor model performance, reliability, and drift; implement updates and improvements as needed.

🛠️ Maintenance & Optimisation

• Maintain and update deployed models to ensure continued alignment with business goals.
• Optimize model latency, cost, and accuracy based on real-world usage data.

🤝 Collaboration & Support

• Work with product and engineering teams to integrate models into applications.
• Support internal teams with prompt design, model usage, and troubleshooting.

⚖️ Responsible AI Practices

• Apply principles of ethical AI development, including privacy, security, and bias mitigation.
• Ensure compliance with internal and external AI governance policies.

• 1+ years’ experience in AI/ML/GI engineering, with a focus on model fine-tuning and deployment.
• Strong experience with PHP, Node, React & Python and libraries like Transformers, Lang Chain, or Hugging Face.
• Familiarity with model evaluation techniques and metrics.
• Experience deploying AI models in production using tools like Docker, Kubernetes, and cloud services (AWS, GCP, or Azure).
• Solid understanding of LLMs or other foundation models and how to work with them effectively.
• Strong analytical, problem-solving, and communication skills.

• Experience with vector databases (e.g. FAISS, Weaviate, Pinecone) or RAG pipelines.
• Knowledge of secure and private model hosting (eg Ollama).
• Certifications in ML, cloud, or AI-related fields.
• Exposure to tools like MLflow, Weights & Biases, or Ray.
• Orchestration automation like n8n

You’ll work on impactful AI solutions without the burden of building from scratch—just smart adaptation, deployment, and ongoing improvement. Help shape how AI is applied responsibly and effectively in the real world.