Our financial services client is looking for a Senior ML engineer with great hands-on coding skills, extensive distributed computing experience and who worked on big data projects with Spark. Candidates must have a proven record of - and can demonstrate - recent experience with large deep learning projects. Ideally, they also had experience working with streaming and Real Time ML, that means inference with very low latency requirements.

Responsibilities:

• You will play a vital role in setting the direction and objectives for your team across project impact, ML system architecture, and upholding machine learning best practices.
• Leverage expertise in adapting standard machine learning techniques to modern parallel computing environments like distributed clusters, multicore Servers, and GPUs.
• Re-evaluate the trade-offs of already shipped features/ML systems, and you can drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate.
• Technically guide team to develop scalable machine learning systems while also influencing engineering culture and standards.
• Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models.
• Suggest, collect, and synthesize requirements and create effective feature roadmap.
• Code deliverables in Tandem with the engineering team

Minimum Qualifications:

• Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical field
• Experience with developing machine learning models at scale from inception to business impact
• Knowledge developing and debugging in C/C++ and Java, or experience with Scripting languages such as Python and/or Shell Scripts.
• Experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects.

Inside IR35 - hybrid working - strong rate - initial 12 month contract

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