Seagate Hiring For 2024 | Intern – Data Science | Apply Here !!

Qualifications:

• Passion for blending the fast-changing technology landscape of Generative AI with HiTech and Manufacturing analytics.
• Strong appetite for constant learning and out-of-the-box thinking.
• Detail-oriented, well-organized, and skilled in time management.
• Effective verbal and written communication abilities.
• Ability to motivate and instill ownership, reliability, teamwork, and commitment in the team.
• Excellent interpersonal skills for developing relationships with different teams and peers.

Experience Includes:

• Experience with machine learning frameworks like scikit-learn, TensorFlow, or PyTorch.
• Experience with machine learning lifecycle platforms (Kubeflow, MLflow) and cloud data services (GCP, AWS).
• Proficiency in at least one major programming language (e.g., Python, Scala, Java) and SQL.
• Collaborative coder, comfortable with Git and code reviews.
• Good knowledge of data management and data mining architecture.
• Ability to proactively identify and resolve issues.

Skills Required:

• Strong expertise in machine learning frameworks and tools.
• Proficiency in programming languages and SQL.
• Knowledge of data management and mining.
• Effective communication and interpersonal skills.
• Strong organizational and time management skills.

Roles & Responsibilities:

• Implement End-to-End ML Pipelines:
  • Assist with implementing end-to-end ML pipelines and deliver scalable production machine learning services.
• Collaborate on ML Model Development:
  • Collaborate with machine learning engineers to build scalable data pipelines and develop new ML models.
• Support ML Workflows:
  • Leverage MLOps tools to support ML workflows including experimentation, training, and production operations.
• Design and Implement Tools and Processes:
  • Design and implement tools and processes for the entire ML Ops lifecycle, including model development, deployment, serving, monitoring, and experimentation.
• Work on Multiple Analytics Streams:
  • Work on multiple streams of analytics, including time series, image, and tabular data.
• Build Accelerators and ML Frameworks:
  • Work on building accelerators and ML frameworks to enhance machine learning processes.