Data Engineer Sr

4 weeks ago

Princeton, United States Munich Re Full time

We're adding to our diverse team of experts and are looking to hire those who are committed to building a culture that enables the creation of innovative solutions for our business units and clients. We will consider a range of experience for this role and the offer will be commensurate with that.

The Company

As a member of Munich Re's US operations, we offer the financial strength and stability that comes with being part of the world's preeminent insurance and reinsurance brand. Our risk experts work together to assemble the right mix of products and services to help our clients stay competitive - from traditional reinsurance coverages, to niche and specialty reinsurance and insurance products.

Job Overview:

We are seeking a highly skilled Senior Machine Learning Engineer to join our AI/ML Engineering GSI IT Team. In this role, you will tackle complex NLP, AI and machine learning challenges, driving forward our ML engineering capabilities. You will be responsible for deploying, implementing, and maintaining advanced machine learning models that enhance our technological solutions and improve decision-making processes.

Key Responsibilities:

  • Develop and implement Machine Learning models, focusing on training & deployment process optimization, including parallelization.
  • Design and build cloud-based data pipelines, integrating ML models into existing software solutions. Write and maintain robust, scalable production-quality code for deployment of ML models and services.
  • Create and deploy inference endpoints (APIs) and optimize compute architectures and data structures.
  • Implement logging and metric generation for models, ensuring comprehensive monitoring and addressing model degradation.
  • Lead the deployment of machine learning models in Azure cloud environments, managing the full lifecycle from development to production.
  • Build CI/CD pipelines for machine learning models using Azure tools to streamline deployment and updates.
  • AI Governance: Ensure compliance with AI governance policies and ethical guidelines, including data privacy, fairness, and transparency in AI systems
  • Work closely with data scientists, engineers, and product managers to review code and integrate ML models into products and services.
  • Collaborate with cross-functional teams to continuously improve and advance technologies and methods for ML systems.
  • Keep up with the latest advancements in machine learning and related technologies to continuously improve model performance.
Qualifications:
  • Strong proficiency in Python and relevant scripting languages, with experience in software development and scripting for Machine Learning.
  • Expertise with ML libraries and frameworks (e.g., Pandas, Numpy, Scikit-Learn, TensorFlow, PyTorch, Databricks, MLFlow, dvc, dbt) and the ability to select the right tools for the use case.
  • Proven experience in optimizing ML training processes, including parallelization techniques to improve model performance.
  • Experience building inference endpoints (APIs) and managing compute architecture for efficient model inference and data handling.
  • Skilled in implementing ML monitoring systems, including logging and metric generation for machine learning models.
  • Very good Azure and data & AI technology skills - specifically: Databricks / Spark, Azure Datalake Store, Azure AI Search, Azure ML, Dataiku.
  • Skilled in cloud platforms (Azure, AWS) for deploying machine learning models and managing model lifecycle, with a focus on addressing model degradation.
  • Experience with CI/CD pipelines for ML, using tools such as Azure Pipelines, or similar.
  • Proficiency with data science tools and best practices for ensuring high-quality and efficient ML workflows.
  • Several years of experience in machine learning, data science, or a related field, with a strong understanding of statistics and data analysis.
  • Extra credit for cloud deployment experience (Azure), containerization (Docker), vector search engines (Azure AI Search), knowledge graphs, ML publications, or competition participation.
Preferred Qualifications:
  • Advanced Degree: Master's degree in Computer Science, Engineering, Mathematics, with 5+ years of ML implementation experience or Ph.D. with 2+ years of hands-on ML Project experience.
  • Experience with Big Data: Strong proficiency with big data technologies such as Azure Databricks and Spark.
  • Leadership Experience: Previous experience leading a team of data scientists or engineers.
Benefits:
  • Competitive employee benefits, including comprehensive health insurance, dental and sports coverage, and opportunities for certified training.
  • Flexibility in work arrangements, including home office options and flexible working hours.
  • A positive, team-oriented environment that fosters mutual trust, creativity, and initiative.
  • Opportunities for career growth within a global, innovative framework.
  • A diverse, multicultural workplace with a strong emphasis on team collaboration and professional development.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

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