Sr Machine Learning Engineer PUNE/Trivandrum
4 weeks ago
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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