Seagate specializes in Global Data Analytics and provides comprehensive solutions for Big data, Generative-AI, and MLOps frameworks and deployments. We are a proactive, solution-focused, and collaborative team that partners with various business groups across the organization to deliver end to end solutions.

Seagate looking for fresher graduates with good knowledge in at least one major programming language (e.g. Python, Scala, Java) and SQL (any variant), having proficient knowledge in machine learning lifecycle platforms (Kubeflow, MLflow) and cloud data services  for the role of Software Engineer Data Science Intern.

Job Designation : Data Science Intern

Qualification :  Bachelor’s degree

Experience : Freshers

Skill Set :

  1. Good in at least one major programming language (e.g. Python, Scala, Java) and SQL (any variant).
  2. Good Knowledge of data management and data mining architecture.
  3. Familiar with machine learning frameworks tools like scikit-learn, TensorFlow, or PyTorch
  4. Expertise with machine learning lifecycle platforms (Kubeflow, MLflow) and cloud data services (GCP, AWS)
  5. A collaborative coder, comfortable with Git and code reviews.
  6. You’re a passionate professional who is up to the challenge of blending the fast-changing technology landscape of Generative AI with the complex and high-impact space of HiTech and Manufacturing analytics.
  7. Strong appetite for constant learning, thinking out of the box, questioning the problems & solutions with the intent to understand and solve better.
  8. You’re uncompromisingly detail oriented, well organized with solid time management skills, and you have solid, effective verbal and written communications abilities.
  9. Ability to motivate people and instill ownership, reliability, teamwork, and commitment in the team.
  10. Excellent interpersonal skills to develop relationships with different teams and peers in the organization.

Job Description :

  1. Assist with implementing end to end ML pipelines and deliver scalable production Machine learning services.
  2. Collaborate with machine learning engineers to build scalable data pipelines and development of new ML models.
  3. Leverage MLops tools to support ML workflows including experimentation, training and production operations.
  4. Design and implement tools and processes for the entire ML Ops including model development, model. deployment, model serving, model monitoring and experimentation.
  5. Work on multiple streams of analytics which includes Time series , image and Tabular data.
  6. Work on building accelerators and ML frameworks.

Location: Pune, India

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