Machine Learning Engineer
About Albany Beck
Albany Beck are a Management Consultancy focused on providing specialist talent and transformative solutions to Financial Services clients. We combine subject matter expertise with innovative delivery models that help clients scale efficiently, while offering meaningful, long-term career opportunities to our people. At Albany Beck, you’ll be choosing to work with an organisation that’s passionate about your learning journey and committed to your professional career and personal development.
Albany Beck are hiring a Machine Learning Developer to support an Onboarding project within a global investment bank.
Key Responsibilities
- Build production-ready machine learning models for content extraction and classification across image and text-based sources.
- Work closely with business stakeholders to understand requirements and iteratively design, develop and refine solutions.
- Collaborate with product managers, engineers and other technical teams across the value stream.
- Create, test and iterate new and existing products and features.
- Design and develop Python-based ML, OCR and Document AI components.
- Support the full product lifecycle, including development, deployment, testing and ongoing production support.
Essential Skills & Experience
- Strong experience in Document AI / Intelligent Document Processing using both traditional techniques and Generative AI with a focus on open-source models to deliver real business outcomes.
- Proven experience delivering Python-based solutions to production, with exposure to machine learning, deep learning, NLP, generative AI, image processing and OCR.
- Hands-on experience with frameworks such as TensorFlow, PyTorch, Hugging Face, SpaCy, OpenCV, Regex or equivalent technologies.
- Experience delivering secure, resilient production code with a strong focus on cybersecurity and API robustness.
Nice to Have
- Experience using PostgreSQL for data storage and management.
- Familiarity with Azure core services, including Azure Virtual Machines, and experience with Azure CLI, Azure Kubernetes Service (AKS) and/or Azure DevOps.
- Experience working in teams that release to production at high cadence using modern engineering practices.