Jobs in Slough, États-Unis

Job Title - AI/ML Engineer

Location - UK

Mode - Remote

Type - Contract (inside IR 35)

• Generative AI Solution Design & Development
  • Design and implement end-to-end Generative AI solutions, including natural language generation (NLG), image generation, code generation, and multi-modal AI applications, on Google Cloud Platform.
  • Leverage and integrate pre-trained Generative AI models from Google's Model Garden and other sources, and adapt them to specific business needs.
  • Implement advanced prompt engineering and RAG (Retrieval-Augmented Generation) strategies to enhance model performance and accuracy.
  • Explore and integrate external tools, APIs, and open-source models to extend Generative AI capabilities.
• Custom GenAI & Model Fine-tuning
  • Lead the fine-tuning, customization, and adaptation of Large Language Models (LLMs) and other generative foundation models using private or proprietary datasets on Vertex AI.
  • Apply techniques such as LoRA (Low-Rank Adaptation), PEFT (Parameter-Efficient Fine-Tuning), and other advanced methods for efficient model adaptation.
  • Experiment with different generative architectures (e.g., Transformers, Diffusion Models) and identify optimal approaches for specific use cases.
  • Develop and implement data pipelines for preparing high-quality datasets for model training and fine-tuning, utilizing GCP data services like BigQuery and Dataflow.
• AI/ML Engineering & MLOps
  • Build, deploy, and manage scalable and robust AI/ML models in production environments using Vertex AI Endpoints and other deployment strategies.
  • Implement MLOps best practices, including CI/CD for ML models, model versioning, lineage tracking, and automated retraining pipelines (e.g., Vertex AI Pipelines, Kubeflow).
  • Monitor model performance, drift detection, and data quality in real-time using Vertex AI Monitoring and other GCP Operations Suite tools.
  • Optimize AI/ML models for performance, cost-efficiency, and latency on GCP infrastructure, including specialized hardware like GPUs and TPUs.
• Research & Innovation
  • Stay abreast of the latest advancements in Generative AI research, Large Language Models, and the broader AI/ML landscape.
  • Evaluate new Google Cloud AI/ML services, features, and third-party tools, recommending their adoption to enhance capabilities.
  • Contribute to internal knowledge sharing, best practices, and the development of reusable components for Generative AI solutions.
• Collaboration & Communication
  • Work closely with data scientists, product managers, software engineers, and business stakeholders to translate complex requirements into actionable Generative AI solutions.
  • Clearly articulate technical concepts, model limitations, and solution trade-offs to both technical and non-technical audiences.
  • Ensure responsible AI practices are integrated into all solutions, addressing ethical considerations, bias, and fairness.

• Bachelor's degree in Computer Science, Machine Learning, AI, or a related quantitative field, or equivalent practical experience.
• 5+ years of experience in AI/ML engineering, with at least 2+ years specifically focused on Generative AI (LLMs, diffusion models, etc.).
• Strong hands-on experience with Google Cloud Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store).
• Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers).
• Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow).
• Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning algorithms.
• Familiarity with MLOps principles and tools for deploying, managing, and monitoring ML models in production.
• Excellent problem-solving skills, with a passion for building innovative and impactful AI solutions.
• Strong communication and collaboration skills.

• Master's degree or Ph.D. in a relevant AI/ML field.
• Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification.
• Hands-on experience with custom fine-tuning of LLMs (e.g., using LoRA, PEFT) and prompt engineering techniques.
• Experience with multi-modal Generative AI models.
• Familiarity with vector databases and vector search technologies (e.g., Vertex AI Vector Search) for RAG implementations.
• Experience with serverless computing (e.g., Cloud Functions, Cloud Run) for deploying AI services.
• Familiarity with ethical AI principles, fairness, accountability, and transparency in AI systems.
• Contributions to open-source AI/ML projects or research publications in Generative AI.