Jobs

    Machine Learning Engineer - India - Allianz Services

    Allianz Services
    Allianz Services India

    1 week ago

    Default job background
    Insurance
    Description

    Key Responsibilities:

    • Lead end-to-end development and delivery of Machine-Learning applications, emphasizing operations and monitoring.
    • Collaborate with multidisciplinary teams to understand business requirements, identify ML workflow requirements, improve processes, and implement new features.
    • Perform software engineering tasks: requirements analysis, design, implementation, testing, deployment, code maintenance, etc.
    • Develop pipelines for deployment and operation of ML applications, following CI/CD best practices.
    • Implement optimization techniques to ensure efficient model inference, reducing computational costs and improving response times.
    • Collaborate with Back-End Engineers to ensure the infrastructure supports the demands of the model, especially concerning GPU resources, memory, and storage.
    • Contribute to architectural and technical documentation

    Requirements:

    • Degree in a quantitative or engineering field like Computer Science, Physics, Mathematics, Statistics, etc.
    • 3-5 years of relevant professional experience in end-to-end data projects, from data cleaning to productionizing ML models.
    • Several years of Python programming experience and overall strong software development skills
    • Demonstrated knowledge of CI/CD pipelines, Jenkins & GitHub actions.
    • Solid understanding of machine learning product lifecycle and the commonly associated components (MLOps)
    • Understanding of multiple machine learning algorithms and techniques.
    • Expertise in ML model deployment (familiar with REST APIs) and monitoring.
    • Experience with containerization technologies such as Docker and Kubernetes.
    • Solid knowledge of at least one major cloud platform, preferably Azure Cloud.
    • Experience coordinating with various technical stakeholders (Engineers, Architects, Data Scientists) to achieve common goals.
    • Strong ability to self-organize, take ownership of topics, and drive them to delivery together with team members.
    • Fluency in English is required; additional languages are a plus.

    Good to Have:

    • Insurance knowledge and proficiency in additional languages.
    • Experience in newer ML approaches (LLM, computer vision, etc.).
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