AI/ML Engineer

Role overview

Responsibilities

• check_circle Design, build, and deploy Machine Learning models.
• check_circle Develop and optimize AI/ML algorithms for production.
• check_circle Build and maintain Generative AI and LLM-based applications.
• check_circle Fine-tune and evaluate Large Language Models.
• check_circle Develop Retrieval-Augmented Generation (RAG) pipelines.
• check_circle Work with structured and unstructured datasets.
• check_circle Perform data preprocessing, feature engineering, and model evaluation.
• check_circle Develop REST APIs using FastAPI or Flask for ML services.
• check_circle Deploy ML models on AWS, Azure, or GCP.
• check_circle Collaborate with Data Engineers, Software Developers, and Product teams.
• check_circle Monitor model performance and improve accuracy.
• check_circle Maintain documentation and follow MLOps best practices.

Basic qualifications

• Python
• Machine Learning
• Deep Learning
• TensorFlow
• PyTorch
• Scikit-learn
• Pandas
• NumPy
• SQL
• Git
• Linux

Preferred qualifications

• Large Language Models (LLMs)
• OpenAI API
• LangChain
• LlamaIndex
• Hugging Face Transformers
• RAG (Retrieval-Augmented Generation)
• Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Prompt Engineering
• Fine-tuning LLMs
• NLP (Natural Language Processing)
• Computer Vision
• FastAPI / Flask
• Docker
• Kubernetes
• MLflow
• Airflow
• AWS SageMaker
• Azure AI Services
• Google Vertex AI

Benefits

• check_circle £37,827.24-£95,825.62 per year