Hiring | Associate Engineer-MLOps

Location: Hadapsar, Pune, Maharashtra, India
Job Req ID: 43368
Work Type: Hybrid
Department: ENG

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About Eaton:

Eaton is a power management company with 2018 sales of $21.6 billion. We are dedicated to improving people’s lives and the environment with power management technologies that are reliable, efficient, safe, and sustainable. Our team embodies core values like ethics, passion, accountability, and commitment to learning. These values help us tackle tough challenges, focusing on what matters most.

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Role Overview:

Eaton Corporation’s Center for Intelligent Power is looking for an Associate Engineer- Machine Learning Operations to develop and maintain the infrastructure and tools required to deploy and maintain machine learning models at scale. This role combines machine learning and software engineering, requiring a close collaboration with other teams to ensure the delivery of business-required features.

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Key Responsibilities:

• Maintain the infrastructure and tools required to deploy machine learning models at scale.
• Develop and maintain Data Engineering pipelines, CI/CD pipelines for machine learning models.
• Develop, train, and validate machine learning models to address business needs.
• Collaborate with data scientists to integrate MLOps principles and best practices.
• Develop and maintain documentation and training materials for machine learning solutions.
• Stay updated with emerging technologies in machine learning and cloud infrastructure.

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Qualifications:

• Bachelor’s or Master's degree in Computer Science, Software Engineering, or a related field.
• Fresher candidates with an understanding of machine learning, software engineering, or related fields are encouraged to apply.

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Skills Required:

• Understanding of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Experience with writing data engineering pipeline code, following coding best practices.
• Familiarity with CI/CD pipelines and containerization technologies like Docker and Kubernetes.
• Understanding of machine learning algorithms such as regression, classification, clustering, and deep learning.
• Proficiency in cloud infrastructure such as AWS, Azure, or GCP.
• Strong analytical and problem-solving skills.
• Excellent communication skills and the ability to work collaboratively with teams.

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Desired Expertise:

• Professional certification in Machine Learning or related field.
• Familiarity with data engineering, data warehousing, and big data technologies such as Hadoop, Spark, or Kafka.
• Experience with DevOps practices and tools.
• Knowledge of monitoring and logging tools like ELK, Grafana, or Prometheus.
• Familiarity with Agile methodologies.

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Tags:

#MLOps #MachineLearning #DevOps #Python #AWS #Azure #GCP #DataEngineering #Kubernetes #Docker #TensorFlow #PyTorch #JobOpening #Hiring #FreshersWelcome