AI Summary
Design, build, and deploy AI-powered solutions using machine learning, deep learning, and generative AI technologies. Collaborate with product managers, data scientists, and software engineers to implement best practices for MLOps, CI/CD, and version control.
Key Highlights
Design, develop, and deploy machine learning and AI models
Build scalable data pipelines and feature engineering workflows
Collaborate with product managers, data scientists, and software engineers
Technical Skills Required
Benefits & Perks
Full-time, permanent employment
Remote work (United Kingdom)
Opportunities to work on real-world problems
Job Description
Job Title: AI Engineer
Location: Remote (United Kingdom)
Employment Type: Full-time, Permanent
Experience: 0–15 Years
Eligibility: Must have the right to work in the UK (No visa sponsorship available)
About The Role
We are seeking a passionate and technically strong AI Engineer to design, build, deploy, and maintain AI-powered solutions. This is a fully remote role within the UK, offering opportunities to work on real-world problems using machine learning, deep learning, and generative AI technologies. Responsibilities and scope will vary based on experience level.
Key Responsibilities
- Design, develop, and deploy machine learning and AI models for production use
- Build scalable data pipelines and feature engineering workflows
- Train, fine-tune, and evaluate ML and deep learning models
- Deploy and serve models via APIs and cloud-based infrastructure
- Monitor model performance, data quality, and model drift
- Work with large, structured and unstructured datasets
- Collaborate with product managers, data scientists, and software engineers
- Implement best practices for MLOps, CI/CD, and version control
- Ensure AI solutions align with security, privacy, and ethical standards
- Document models, workflows, and system architectures
- Strong programming skills in Python
- Solid understanding of machine learning algorithms and evaluation techniques
- Experience with deep learning frameworks (PyTorch, TensorFlow, or Keras)
- Proficiency in data processing and analysis (NumPy, Pandas)
- Experience building and consuming REST APIs
- Familiarity with cloud platforms (AWS, Azure, or GCP)
- Knowledge of Git and collaborative development workflows
- Understanding of data structures, algorithms, and software engineering principles
- Experience with Generative AI and LLMs (prompt engineering, fine-tuning, RAG)
- NLP or Computer Vision experience
- MLOps tools such as MLflow, Kubeflow, Airflow
- Containerisation using Docker and orchestration with Kubernetes
- Experience with vector databases (FAISS, Pinecone, Weaviate)
- Knowledge of responsible AI, explainability, and bias mitigation
- Experience with big data tools (Spark, Kafka)