Machine Learning Engineer

ARM

Ringway

Sur place

GBP 90 000 - 150 000

Plein temps

Il y a 3 jours
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Résumé du poste

ARM is seeking a Senior AI & ML Engineer to lead design, development and deployment of cutting-edge AI and Generative AI solutions. You will shape technical strategy, build production-grade AI systems and drive engineering best practices across client engagements.

You will design and deploy RAG-based solutions, leverage PyTorch and transformer architectures, and implement scalable MLOps with Docker/Kubernetes on GCP.

Qualifications

  • Extensive experience in AI/ML engineering or Applied AI.
  • Expert-level Python and PyTorch skills.
  • Strong understanding of LLMs, transformer architectures and model optimisation.
  • Experience designing and deploying RAG solutions and AI agents.
  • Strong cloud experience, ideally within Google Cloud Platform (GCP).
  • Experience with Docker, Kubernetes and modern MLOps tooling.
  • Proven experience taking AI solutions from concept to production at scale.
  • Strong communication skills with both technical and business stakeholders.
  • Experience leading technical design and mentoring engineers.

Responsabilités

  • Lead the design and delivery of AI, ML, Agentic AI and RAG-based solutions.
  • Build and deploy production-grade models using Python and PyTorch.
  • Design scalable MLOps frameworks, CI/CD pipelines and deployment strategies.
  • Develop model serving capabilities using cloud-native technologies and containers.
  • Create reusable frameworks, tooling and templates to accelerate AI adoption.
  • Drive model monitoring, drift detection, testing and governance.
  • Collaborate with architects, data scientists and engineers to deliver value.
  • Mentor engineers and promote engineering excellence.
  • Support technical strategy and innovation initiatives.

Connaissances

Python
PyTorch
LLMs
Transformer architectures
MLOps
Docker
Kubernetes
GCP
Stakeholder comms
Mentoring engineers

Outils

Vertex AI
MLFlow
KServe

Description du poste

The Opportunity

A leading financial consultancy is seeking a Senior AI & ML Engineer to lead the design, development and deployment of cutting-edge AI, Machine Learning and Generative AI solutions. You'll play a key role in shaping technical strategy, building production-grade AI systems and driving engineering best practices across complex client engagements.

Key Responsibilities
  • Lead the design and delivery of AI, Machine Learning, Agentic AI and RAG-based solutions.
  • Build and deploy production-grade models using Python, PyTorch and modern transformer architectures.
  • Design scalable MLOps frameworks, CI/CD pipelines and model deployment strategies.
  • Develop model serving capabilities using cloud-native technologies and containerised environments.
  • Create reusable frameworks, tooling and templates to accelerate AI adoption.
  • Drive model monitoring, drift detection, testing and governance best practices.
  • Collaborate with architects, data scientists, platform engineers and stakeholders to deliver business value.
  • Mentor and coach engineers while promoting engineering excellence across teams.
  • Support technical strategy, research and innovation initiatives.
What We're Looking For
  • Extensive experience in AI Engineering, Machine Learning Engineering or Applied AI.
  • Expert-level Python and PyTorch skills.
  • Strong understanding of LLMs, transformer architecture and model optimisation.
  • Experience designing and deploying RAG solutions and AI agents.
  • Strong cloud experience, ideally within Google Cloud Platform (GCP).
  • Experience with Docker, Kubernetes and modern MLOps tooling.
  • Proven experience taking AI solutions from concept to production at scale.
  • Strong communication skills with both technical and business stakeholders.
  • Experience leading technical design and mentoring engineers.
Desirable Experience
  • Financial services or regulated industry experience.
  • Experience within enterprise-scale AI environments.
  • Knowledge of Vertex AI, KServe and MLFlow.
  • Feature Store and Model Registry experience.
  • Experience building internal AI platforms or reusable AI frameworks.
  • Cloud certifications and advanced academic qualifications are beneficial.
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