Machine Learning Engineer

apartmentRobert Half placePleasanton calendar_month 

Robert Half is looking for two AI Engineers for our growing team with a .NET focus, who will be responsible for designing, modifying and developing software programming applications, ensuring customer satisfaction is met by all team members.

This is a long term, fully remote role.

If interested, please apply to this job post with your updated resume for Suman Sandhu to review.
  • Application Development & AI Integration (70%)
  • Be an integral part of the application development team, with a special focus on implementing the business logic for our AI-based auto take rules engine (Python, COSMOS, Machine Learning, Data Science). Review, analyze, and modify existing proprietary applications to correct errors, improve performance, and add new features while exceeding coding standards.
  • Technical Architecture & Design (10%)
  • Develop technical architectures, design patterns, and implementation plans for the team to follow in the development process.
  • Troubleshooting & Issue Resolution (10%)
  • Troubleshoot and resolve production issues reported by customers or the internal software support team, ensuring timely and effective fixes.
  • Agile Scrum Participation (10%)
  • Participate in Sprint Planning, Daily Standups, Sprint Reviews, and Sprint Retrospectives as part of the Agile Scrum software development lifecycle.

Educational Background:

o Bachelor’s degree or relevant experience, which is great and often required.
  • AI/ML Experience:

o 5+ years in AI, ML, or Data Science roles.

o Strong technical hands-on experience in Python.

o Knowledge of machine learning fundamentals, model variants, and end-to-end ML lifecycle.

o Experience with common ML libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, Pandas.
  • Cloud Expertise:

o Hands-on experience with major cloud providers (GCP, AWS, or Azure) is essential for an MLOps engineer.

o Familiarity with Azure deployment, monitoring, and cloud resource optimization.
  • MLOps Expertise:

o Experience designing and implementing MLOps platforms, optimizing scalability, efficiency, and workflows.

o Familiarity with monitoring and improving performance.
  • Technical Tools:

o Experience with Git and Bitbucket for version control.

o JIRA/Confluence for project tracking and documentation.

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