Machine Learning Engineer

London- Hybrid

£ Salary - commensurate with experience

An exciting opportunity has arisen, to join a market leading financial analytics organisation in an Al/ML role. This company are renowned for their superb working culture and proactivity when it comes to developing their employees.

Key responsibilities:

• Enhance and scale the company's AWS-based infrastructure to ensure the efficient, reliable delivery of ML and AI solutions, including the integration of LLM.
• Architect and design groundbreaking machine learning techniques tailored to financial tasks within Knowledge Graphs, creating innovative solutions that extend beyond traditional applications.
• Work closely with data scientists and ML engineers to integrate and manage diverse ML and NLP models within production environments effectively. Offer expert advice on model selection and deployment strategies.
• Manage the entire software development lifecycle, from the initial design and coding through to testing and the deployment of financial AI applications.

Skills required:

• Demonstrated expertise in cloud architecture (primarily AWS) and familiarity with a broad range of services.
• Solid understanding of Natural Language Processing/Machine Learning/Deep Learning fundamentals and their real-world applications, evidenced by a successful history of model development and deployment.
• Python, with strong skills in Docker and API development.
• Excellent communication abilities, capable of engaging both technical and business audiences alike, and leading cross-functional projects.
• Knowledge of major database architectures including MongoDB, SQL, NoSQL, and Vector databases.

Experience with knowledge graphs and architecting LLM-powered solutions would be desirable, but not essential, along with existing experience within the financial sector.

The role requires at least 3 years of profound software engineering experience, with a focus on AI/ML solutions in production environments.

Please apply if you are interested in full details.