Lead ML Engineer
Casablanca, MA, 20060
Allianz
As an international financial services provider, Allianz offers worldwide products and solutions in insurance and asset management.| Operations | Professional | | Allianz Services | Full-Time | Permanent
We are looking for Machine Learning Engineers who are excited to work on Machine Learning/Deep Learning projects. The ideal candidate will have good Machine Learning/Deep learning expertise, and hands on experience solving complex real-world ML/DL problems. We want people who are excited to solve the hard problems, eager to work with a larger team of data scientists & engineers and ready to make business impact in areas related to Pricing, Claims, Sales, Marketing, Operations or any other ongoing research into the organisation
What You Do
- Enable the successful development and deployment of Machine-Learning applications from conceptualization to production with an emphasis on operations and monitoring.
- Detect, analyze, address bottlenecks and painpoints along the ML workflow with patterns and practices that will improve quality and speed.
- Listen and engage with the product team members to ensure their adoption in a collaborative and influential fashion so that siloed behavior is prevented.
- Follow standard industry processes such as Agile, DevOps, version control, model management, deployment and operation of ML applications.
- Keep hands-on by occasionally performing software engineering tasks such as: requirements analysis, design, development, testing, deployment, code maintenance, data pipelines, etc.
- Contribute and review architectural and other technical documentation, acting as a sparring partner.
- Mentor / train more junior colleagues in areas of expertise.
What You Bring
- Master's degree or PhD in a quantitative or engineering field like Computer Science, Physics, Mathematics or Statistics.
- Fluency in English is a must, German is a plus.
- Previous experience in business related functions (e.i. Sales, Operations, Claims, Underwriting, Investment Management, Asset Management, Consulting, Product Development, Finance, Market Management, Digital / Tech etc.) is a plus.
Preferred Qualifications:
- At least 5 years of hands-on experience as part of end-to-end ML projects.
- Expertise in technical documentation practices (e.g. Arc42).
- Knowledge of continuous monitoring of performance of ML applications and tools and environments (Grafana, Prometheus, Kubernetes, CI-CD, etc.).
- Advanced understanding of cloud technologies (AWS and Azure).
- Good understanding of technical feasibility of data-driven products and services.
- Experience coordinating with various technical stakeholders (Engineers, Architects, Data Scientists) to achieve a common goal.
- Strong ability to self-organize, take ownership of topics and drive them to delivery together with others team members.
- Experience in monitoring data drift in a running ML system.
- Insurance knowledge and additional languages are a plus.
#LI-JK1
Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges, is what makes us a unique employer. Together we can build an environment where everyone feels empowered and has the confidence to explore, to grow and to shape a better future for our customers and the world around us.
We at Allianz believe in a diverse and inclusive workforce and are proud to be an equal opportunity employer. We encourage you to bring your whole self to work, no matter where you are from, what you look like, who you love or what you believe in.
We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, disability or sexual orientation.
Great to have you on board. Let's care for tomorrow.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS Azure Computer Science Consulting Data pipelines Deep Learning DevOps Engineering Finance Grafana Kubernetes Machine Learning Mathematics PhD Physics Pipelines Research Statistics Testing
Perks/benefits: Career development Insurance
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