Eaton is Hiring Freshers for Associate Engineer Role – 2025 Recruitment for BE/BTech/BSc/ME/MTech/MSc Graduates

• Maintain the infrastructure and tools required to deploy machine learning models at scale.
• Develop and maintain Data Engineering pipelines, continuous integration, and deployment (CI/CD) pipelines for machine learning models.
• Develop, train, and validate machine learning models to address business needs.
• Understanding the challenges in productionizing machine learning software and collaborating with data scientists to ensure that the software best practices, templates and other MLOps principles are integrated to reduce cycle time.
• Develop and maintain documentation and training materials for machine learning solutions.
• Keep up to date with emerging technologies and trends in machine learning and cloud infrastructure.
  

Qualifications:

•  Requires a minimum of a Bachelor level degree in computer science or equivalent software engineering discipline.

•    Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
 

Skills:

•    Fresher with understanding in machine learning, software engineering, or related field.
•    Understanding of machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
•    Understanding of writing data engineering pipeline code with coding best practices.
•    Understanding of CI/CD pipelines and containerization technologies such as Docker and Kubernetes.
•    Understanding of algorithms such as regression, classification, clustering and deep learning.
•    Strong analytical and problem-solving skills.
•    Excellent communication skills and ability to work collaboratively with other teams."

•    Fresher with understanding in machine learning, software engineering, or related field.
•    Understanding of  machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
•    Understanding of cloud infrastructure such as AWS, Azure, or GCP.
•    Understanding of writing data engineering pipeline code with coding best practices.
•    Understanding of CI/CD pipelines and containerization technologies such as Docker and Kubernetes.
•    Understanding of algorithms such as regression, classification, clustering and deep learning.
•    Understanding of software engineering best practices, including version control, testing, and deployment.
•    Strong analytical and problem-solving skills.
•    Excellent communication skills and ability to work collaboratively with other teams.
•    Ability to manage multiple projects and priorities in a fast-paced environment.

Desired Expertise (in one or more of the following areas):
•    Professional certification in Machine Learning or related field.
•    Understanding of data engineering and data warehousing concepts.
•    Understanding of big data technologies such as Hadoop, Spark, or Kafka.
•    Familiarity with DevOps practices and tools.
•    Familiarity with monitoring and logging tools such as ELK, Grafana, or Prometheus.
•    Familiarity with Agile methodologies.

Please apply soon before the link expire