Job Opportunity: Machine Learning Engineering Manager (NLP/LLMs) | Global Software Company
On behalf of our client, a global software company providing innovative solutions within the financial and regulatory space, we are seeking a highly skilled Machine Learning Engineering Manager. This is a fantastic opportunity to lead a talented team of ML engineers and drive cutting-edge projects focused on NLP, Large Language Models (LLMs), and other advanced machine learning technologies.
About the Role: As the Machine Learning Engineering Manager, you will lead a team of 5 engineers (with potential for growth) to deliver key machine learning projects related to analytics, Retrieval-Augmented Generation (RAG), and A/B testing. You’ll work closely with cross-functional teams to ensure seamless integration of ML models into production environments, particularly within SaaS and ML-Ops frameworks.
Key Responsibilities:
Team Leadership & Development:
- Lead and mentor a team of machine learning engineers, providing guidance on best practices, code reviews, and CI/CD pipelines.
- Foster a collaborative, inclusive team culture while ensuring alignment with the company’s broader goals.
Technical Expertise:
- Oversee the design and implementation of distributed systems and manage ML infrastructure using Kubernetes and Kafka.
- Utilize JVM languages (Java, Kotlin, Groovy, Scala, Clojure) to scale ML applications.
- Ensure cost efficiency by managing COGS and utilizing observability tools like Grafana to monitor system health.
- Take a hands-on approach to problem-solving and incident management, ensuring swift resolution of customer issues.
Product & Stakeholder Engagement:
- Collaborate with product teams to align engineering efforts with business goals and ensure a strong product-focused mindset.
- Drive the deployment of ML models in the financial and regulatory sectors, with expertise in fraud detection, regulatory compliance, and anti-money laundering.
- Engage with stakeholders to provide technical guidance and subject matter expertise.
Innovation & Optimization:
- Lead initiatives in Retrieval-Augmented Generation (RAG) and A/B testing to optimize and validate ML models.
- Champion continuous improvement of ML pipelines and systems, leveraging new technologies and industry best practices.
Incident Management:
- Oversee the incident management process, ensuring issues affecting system performance or customer experience are quickly resolved.
Qualifications:
- Proven experience managing and scaling engineering teams, particularly in SaaS or ML-Ops environments.
- Expertise in JVM languages (Java, Kotlin, Groovy, Scala, Clojure), Kubernetes, and Kafka.
- Strong background in the banking, fintech, or finance sectors, with a focus on fraud detection, regulatory compliance, and anti-money laundering.
- Experience with CI/CD pipelines, distributed systems, and monitoring tools like Grafana.
- Experience with RAG and A/B testing is a plus.
- Excellent communication skills and the ability to engage with stakeholders at all levels.
Why Join? This is an exciting opportunity to join a forward-thinking company at the forefront of machine learning innovation. You will lead a talented team and work on impactful projects that drive financial technology forward in a collaborative and supportive environment.
Application Process: Interested candidates should submit their resume and cover letter, outlining relevant experience and why they are a great fit for this role.
