Overview

We are seeking an AI Research Engineer to design, develop, and deploy scalable machine learning systems and AI-powered features.

Responsibilities

• Design and develop AI features from data ingestion through real-time model inference.
• Build scalable, cost-efficient, and observable machine learning systems and services.
• Develop training and inference pipelines for LLM, computer vision, and multimodal AI models.
• Create model evaluation frameworks, including offline evaluation, online experiments, and user feedback integration.
• Collaborate with software engineering, data, and product teams to deliver AI-powered features.
• Deploy, monitor, and maintain machine learning models using containerised and cloud-based infrastructure.
• Investigate production incidents, improve system reliability, and optimise operational performance.
• Optimise training and inference costs through batching, quantisation, mixed precision, and GPU resource management.

Qualifications

• Role Summary
• We are seeking an AI Research Engineer to design, develop, and deploy scalable machine learning systems and AI-powered features. The role focuses on building LLM, computer vision, and multimodal machine learning pipelines, deploying models into production, and improving system reliability, performance, and cost efficiency.
• Strong proficiency in Python and machine learning frameworks such as PyTorch or TensorFlow.
• Knowledge of MLOps tools such as MLflow, Weights & Biases, DVC, Airflow, or Prefect.
• Understanding of GPU optimisation, ONNX, TensorRT, batching, and mixed precision techniques.
• Familiarity with vector databases, retrieval-augmented generation (RAG), and LLM fine-tuning approaches.
• Knowledge of observability and monitoring tools such as Prometheus, Grafana, or OpenTelemetry.
• Strong analytical, problem-solving, and collaboration skills.
• Bachelor?s or Master?s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 3?5+ years of experience in applied machine learning, AI engineering, or software engineering.
• Understanding of statistics, experimentation, model evaluation, and real-world performance analysis.
• Hands-on experience with LLMs, computer vision, or multimodal AI systems.
• Ability to balance research innovation with production engineering requirements.
• Strong ownership mindset and experience working in cross-functional teams.
• Excellent communication and technical documentation skills