AI ML Engineer

Overview

Were Hiring: 3–5 AI/ML Engineers (Full-Stack AI Expertise) for our LHR office

Location: (On-site)

Employment Type: Full-time

Positions Open: 1 Engineer

Experience Level: Mid to Senior

About the Opportunity

We are expanding our AI engineering team and are looking to hire 3–5 talented AI/ML Engineers with strong, practical fluency across the core disciplines of Artificial Intelligence. You will join a fast-growing group that builds scalable, production-ready AI systems using cutting-edge tools and methodologies.

Were seeking engineers who understand the full AI lifecycle—from data to deployment—and who are excited to collaborate, innovate, and deliver high-impact AI solutions.

Key Responsibilities

• Develop, train, evaluate, and deploy machine learning and deep learning models for real-world applications.
• Build and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, experimentation, and production deployment.
• Work extensively with Python, TensorFlow, PyTorch, scikit-learn, and modern AI frameworks.
• Apply techniques across:
  • Supervised & Unsupervised Learning
  • Deep Learning (CNNs, RNNs, Transformers)
  • NLP, Computer Vision, Speech & Multimodal AI
  • Reinforcement Learning
  • Generative AI and LLM-based solutions
• Participate in data engineering tasks such as ETL workflows, dataset curation, and feature store management.
• Implement MLOps best practices including model versioning, CI/CD for ML, monitoring, and performance tracking.
• Collaborate with cross-functional teams to translate requirements into scalable AI solutions.
• Keep up with advancements in AI tooling, architectures, and production techniques.

Qualifications (for all positions)

• Bachelors degree in Computer Science, Software Engineering, Data Science, Electrical/Computer Engineering, or a related technical field.
• Strong programming skills in Python.
• Hands-on experience with at least one major ML framework (PyTorch, TensorFlow, or JAX).
• Experience deploying models in cloud environments (AWS, Azure, or GCP) and containerized systems (Docker, Kubernetes).
• Solid understanding of:
  • Probability, statistics, and optimization
  • Neural networks and ML fundamentals
  • Data structures and algorithms
• Experience with LLM fine-tuning, vector databases, or RAG pipelines is a plus (not required).
• Strong analytical, problem-solving, and communication skills.

Why Join Us?

• Join a rapidly growing AI team with multiple openings and room for career advancement.
• Work on impactful AI/ML projects using cutting-edge tools and infrastructure.
• Competitive compensation and benefits package.
• Collaborative, high-energy environment where your ideas and expertise matter.
• Opportunities to specialize in areas of interest (NLP, Computer Vision, MLOps, Generative AI, etc.).