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Job description
Remote: Hybrid
Staff Machine Learning Engineer – AI/ML Information Extraction
Remote (Or Hybrid If London based – 2 days)
Company Overview
My client is a fast-growing, product-led technology business operating within a specialist professional services sector. They provide a SaaS platform used by organisations globally to improve business development, marketing, and knowledge management processes.
The company has recently launched an advanced AI-driven product focused on automating complex, manual workflows and enabling users to generate high-quality outputs more efficiently using organisational data.
With a distributed team across the UK and US, the business is backed by private investment and is entering an exciting phase of growth, with a strong focus on innovation, AI, and scalable product development.
The Role
My client is looking for a Staff Software Engineer – AI/ML with expertise in Information Extraction to play a key role in advancing their AI capability.
This is a hands-on technical leadership role, focused on building and scaling AI-powered products. You will work with modern machine learning approaches, including large language models and agentic workflows, alongside cloud-based AI platforms.
The successful candidate will help define technical direction, establish best practices, and deliver robust, scalable AI/ML systems. You will also mentor engineers and contribute to building a high-performing AI-focused team.
This is an opportunity to work on greenfield and evolving AI products with real-world impact.
Key Responsibilities
Project Ownership
- Lead the design, planning, and delivery of AI/ML initiatives
- Own end-to-end lifecycle of models and systems, from experimentation to production
Cross-Functional Collaboration
- Partner with Product, Engineering, and DevOps teams to integrate AI capabilities
- Ensure smooth data flow, deployment, and system interoperability
Technical Leadership
- Provide guidance on tools, frameworks, and AI/ML best practices
- Explore and implement advanced approaches including LLMs and agent-based systems
Mentorship & Communication
- Support and mentor engineers through coaching and code reviews
- Communicate effectively across technical and non-technical stakeholders
Problem Solving & Optimisation
- Identify and address challenges in AI workflows
- Improve system performance, scalability, and reliability
Model Performance & Governance
- Enhance model accuracy and robustness
- Address data quality, bias, and interpretability considerations
- Ensure compliance with security and privacy standards
Documentation & Knowledge Sharing
- Maintain clear documentation and internal best practices
- Support continuous improvement and onboarding
Skills & Experience
- 7+ years in AI/ML engineering, including production deployments
- 3+ years in a technical leadership capacity
- Strong programming skills (Python, Java, or Rust)
- Experience in machine learning, data engineering, and information extraction
- Knowledge of LLMs, evaluation frameworks, and modern AI workflows
- Experience with cloud platforms (AWS, GCP, or Azure)
- Understanding of distributed systems and large-scale data pipelines
- Experience with MLOps, CI/CD, and microservices architecture
- Familiarity with AI-assisted or agent-based development tools
- Strong stakeholder collaboration and communication skills
- Agile/Scrum experience
- Degree in a relevant technical field
Tech Environment
- Python, Java
- Cloud platforms AWS
- Containerisation and infrastructure-as-code tools
- Relational and non-relational databases
- Amazon Bedrock, Sagemaker, Vertex AI
- Datadog, Databricks, MLFlow, Grafana, OTel
- Claude, Gemini, ChatGPT, open-weight LLM models
- Terraform, Docker, K8s
- RMDBs, Graph DBs, Vector DBs
- Claude Code
- Github (and Github actions)
Benefits
- Competitive salary
- 25 days’ annual leave + bank holidays
- Sick pay package
- Flexible/remote working
- Enhanced parental leave
- Pension scheme
- Central London office facilities
- Career progression opportunities
