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About the Role
Job Title: Senior Solutions Architect
Location: London, UK
Nationality: British (Mandatory)
Required Skills
- Prior experience in a technical role oriented towards pre-sales, partners, or consulting, with a strong component of interaction with partners and clients (e.g., Solutions Architect, Sales Engineer, Implementation Consultant).
- Excellent communication and presentation skills, with the ability to interact effectively with both technical and non-technical audiences.
- Experience in writing technical proposals and responding to tenders (RFPs/tenders).
- Experience in independently conducting product demonstrations and technical workshops.
- Solid knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, Azure ML), including sovereign, on-premise, and hybrid deployment models.
- Proficiency in MLOps tools and practices: CI/CD, monitoring and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow).
- Good knowledge of Docker and Kubernetes for containerizing AI workloads.
- Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model deployment formats (ONNX,.safetensors, Hugging Face Model Hub).
- Experience in sizing GPU infrastructures for LLM model inference or training (memory, throughput, hardware categories ranging from A10 to H200).
- Experience in evaluating and benchmarking LLM performance (accuracy, latency, throughput).
- Practical skills in Python and SQL programming, as well as knowledge of ML libraries and frameworks such as PyTorch, TensorFlow, and Hugging Face.
- Bachelor's or Master's degree in computer science, data science, engineering, or related field.
- Availability to travel as required for meetings, conferences, and projects.
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Desired Qualifications
- Experience with computer vision, speech processing, vision-language, and other multimodal models.
- Experience in optimizing, quantifying, or deploying AI models on edge devices.
- Practical experience in the design of RAG (Retrieval-Augmented Generation) pipelines and/or multi-agent systems.
- Experience in designing data architectures (batch and streaming) and in using Big Data technologies.
- Knowledge of the issues related to data privacy and AI ethics, including GDPR compliance and a good understanding of the European AI Act.
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Advantages & Benefits
- Equal pay guaranteed.
- Signing bonus.
- Relocation package (if applicable).
- Access to a training budget in accordance with internal policy.
- Hybrid work model.
- Flexible working hours.
- Language courses and catering options at preferential rates.
- Work in a dynamic and innovative environment, at the heart of cutting-edge technologies.
- Structured career plan with numerous opportunities for learning and knowledge sharing.
- A progressive company with a culture focused on employee well-being and satisfaction.
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Skills
Solutions Architect
Sales Engineer
Implementation Consultant
Communication Skills
Technical Proposals
Product Demonstrations
Cloud Platforms
AI Services
MLOps
Docker
Kubernetes
Python
SQL
Machine Learning
Data Privacy
AI Ethics
Location