Senior AI/ML Engineer, UK

Vector8 designs and delivers production-grade AI solutions, particularly for financial services and retail. The Senior AI/ML Engineer designs, builds, integrates, and operates production AI systems, from client scoping through monitoring and continuous improvement, while helping clients develop reusable AI foundations.

Responsibilities:

• Design and build agents and AI workflows, including tool integration, orchestration, guardrails and human validation steps
• Integrate LLMs, retrieval and classical ML or speech models with clients' existing systems and data
• Make these solutions reliable in production through systematic evaluation, tracing, fallback strategies, and cost and latency control
• Apply software engineering best practices: testing, CI/CD, modular design and documentation
• Address the requirements of regulated industries, such as security, compliance, access control and integration with legacy systems
• Own solutions end to end, from scoping with the client to production monitoring and continuous improvement
• Work closely with vector8's engineers and project managers, as well as with client architects and business teams
• You will help build AI foundations that our clients can reuse and extend as they scale from individual use cases to company-wide capabilities
• Design and build LLM agents that use tools and interact with enterprise systems and data
• Orchestrate multi-step and multi-agent workflows, with human validation and hand-off where needed
• Define clear boundaries for each agent through typed tool contracts, structured outputs, guardrails and access policies
• Connect agents to other systems through open protocols such as MCP and A2A, and through well-designed APIs
• Choose the most appropriate architecture for each problem, whether an agent, a deterministic workflow or a classical ML solution
• Evaluate AI solutions systematically against datasets to generate meaningful performance metrics
• Write clean, modular, and well-documented code in Python (FastAPI, Pydantic, asyncio)
• Apply best practices in:
• Testing (unit, integration, end-to-end)
• CI/CD (GitHub Actions, GitLab CI, Argo CD)
• Observability (logging, monitoring, tracing)
• Ensure security and compliance (data protection, access controls, encryption)
• Integrate models and code into CI/CD pipelines for seamless deployment
• Deploy and monitor AI solution in production
• Design and implement MLOps pipelines for:
• Model training, fine-tuning, and evaluation
• Model versioning and lineage tracking
• A/B testing and canary deployments
• Ensure scalability and reliability (auto-scaling, fault tolerance, disaster recovery)
• Collaborate with data engineers to build data pipelines (batch, streaming, real-time)
• Work closely with product owners, DevOps, and quality assurance in an agile, cross-functional team
• Mentor junior engineers and promote best practices in AI/ML and software engineering
• Translate product requirements into technical solutions and architectural decisions
• Document architectures, decisions, and best practices for internal and client-facing use
• Develop relationships with internal and external stakeholders, including clients and partners
• Design, implement, and deploy distributed, high-volume, high-performance, low-latency machine learning solutions, with a focus on GenAI models, and especially LLM integrations and API-driven architectures
• Take ownership of your models throughout their entire lifecycle:
• Data exploration and cleaning to build reproducible, versioned datasets
• State-of-the-art research to identify the best architectures for the problem (e.g., transformers, RAG, fine-tuning)
• Implementation, training, and optimization in reproducible environments
• Deployment, monitoring, and maintenance in production
• Optimize models for performance, latency, and cost efficiency, especially in LLM serving and inference
• Stay ahead of the latest AI and ML architectures (transformers, Mixture of Experts, sparse attention)
• Experiment with cutting-edge techniques (quantization, distillation, speculative decoding)
• Evaluate and benchmark open-source and proprietary models (Llama, Mistral, Mixtral, GPT-4, Claude)
• Bring your own ideas through vector8’s ideation process
• Contribute to vector8’s AI accelerators (reusable components for common industry problems)
• Embrace a strategic and continuous improvement mentality to drive innovation