Eaton is Hiring Associate Engineer – Machine Learning | Freshers | Pune

Job Description

Eaton is hiring Associate Engineer – Machine Learning for its Hadapsar, Pune office. This opportunity is ideal for fresh graduates and early-career professionals who are passionate about Machine Learning, MLOps, Data Engineering, Cloud Computing, Artificial Intelligence, and Software Engineering. If you're looking to work on scalable machine learning solutions while learning modern AI infrastructure and cloud technologies, this is an excellent opportunity to begin your career.

As an Associate Engineer – Machine Learning, you will develop and maintain machine learning infrastructure, build data engineering pipelines, support CI/CD workflows, collaborate with data scientists, and contribute to deploying production-ready AI solutions using modern MLOps practices.

𝐂𝐨𝐦𝐩𝐚𝐧𝐲: Eaton
𝐑𝐨𝐥𝐞: Associate Engineer – Machine Learning
𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: Hadapsar, Pune, Maharashtra
𝐖𝐨𝐫𝐤 𝐌𝐨𝐝𝐞: Hybrid
𝐉𝐨𝐛 𝐓𝐲𝐩𝐞: Full-Time
𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 0–2 Years

𝐀𝐛𝐨𝐮𝐭 𝐄𝐚𝐭𝐨𝐧

Eaton is a global intelligent power management company committed to improving quality of life and protecting the environment through innovative technologies. Operating in more than 180 countries, Eaton delivers solutions across data centers, industrial automation, aerospace, mobility, utilities, and commercial infrastructure.

With a strong focus on digital transformation, artificial intelligence, sustainability, and innovation, Eaton provides engineers with opportunities to work on next-generation technologies while building rewarding global careers.

𝐉𝐨𝐛 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

As an Associate Engineer – Machine Learning, you will support the development, deployment, and maintenance of machine learning models and MLOps infrastructure. You will work closely with software engineers and data scientists to build scalable AI solutions, automate machine learning workflows, and improve production deployment processes.

This role offers valuable exposure to Machine Learning, Cloud Platforms, Data Engineering, MLOps, CI/CD, Docker, Kubernetes, and enterprise AI development.

Roles & Responsibilities

- Develop and maintain infrastructure required for deploying machine learning models at scale.

- Build and maintain data engineering pipelines for machine learning workflows.

- Develop, train, validate, and support machine learning models for business applications.

- Create and maintain CI/CD pipelines for machine learning deployments.

- Collaborate with data scientists to productionize AI solutions using MLOps best practices.

- Develop technical documentation and training materials for machine learning solutions.

- Monitor and improve machine learning deployment processes.

- Stay updated with emerging technologies in AI, machine learning, cloud computing, and MLOps.

- Follow software engineering best practices, including testing, version control, and deployment.

- Work effectively with cross-functional global engineering teams.

Qualifications & Eligibility

- Bachelor's degree in Computer Science, Software Engineering, or a related discipline.

- Fresh graduates and candidates with 0–2 years of experience are eligible.

- Basic understanding of machine learning concepts and software engineering.

- Strong analytical, problem-solving, and communication skills.

- Ability to work collaboratively in fast-paced engineering environments.

Skills Required

- Machine Learning

- TensorFlow

- PyTorch

- Scikit-learn

- Python

- Data Engineering

- Cloud Computing (AWS, Azure, or GCP)

- CI/CD Pipelines

- Docker

- Kubernetes

- Regression & Classification Algorithms

- Clustering

- Deep Learning

- Software Engineering

- Version Control

- Problem Solving

- Communication Skills

𝐏𝐫𝐞𝐟𝐞𝐫𝐫𝐞𝐝 𝐒𝐤𝐢𝐥𝐥𝐬

- MLOps

- Hadoop

- Apache Spark

- Apache Kafka

- Data Warehousing

- DevOps

- ELK Stack

- Grafana

- Prometheus

- Agile Methodologies

- AI Model Deployment

- Research & Innovation

𝐖𝐡𝐲 𝐉𝐨𝐢𝐧 𝐄𝐚𝐭𝐨𝐧?

- Start your AI career with a globally recognized engineering company.

- Work on real-world Machine Learning and MLOps projects.

- Gain hands-on experience with cloud infrastructure and scalable AI systems.

- Collaborate with experienced data scientists and software engineers.

- Learn modern DevOps, CI/CD, and containerization technologies.

- Grow through continuous learning, mentorship, and global collaboration.

- Contribute to innovative solutions that support sustainable technologies worldwide.

𝐂𝐚𝐫𝐞𝐞𝐫 𝐆𝐫𝐨𝐰𝐭𝐡 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬

This role provides an excellent foundation for careers such as:

- Machine Learning Engineer

- MLOps Engineer

- AI Engineer

- Data Engineer

- Cloud Engineer

- Software Engineer

- Data Scientist

- DevOps Engineer

- Platform Engineer

- AI Solutions Engineer

𝐖𝐡𝐨 𝐒𝐡𝐨𝐮𝐥𝐝 𝐀𝐩𝐩𝐥𝐲?

- Fresh graduates interested in Machine Learning and Artificial Intelligence.

- Candidates with knowledge of TensorFlow, PyTorch, or Scikit-learn.

- Individuals interested in Cloud Computing, MLOps, and Data Engineering.

- Aspiring AI engineers looking to gain hands-on industry experience.

- Candidates eager to build scalable machine learning solutions with a global engineering leader.