Tech Mahindra (Americas) Inc.

Tech Mahindra (Americas) Inc.

AI/ML Engineer

San Jose, California, USA · Full-time

Sponsorship not specified$140k-$145kDetected 72 days ago
PythonAlgorithmsAWSGCPCloud PlatformsMachine LearningTensorFlowPandasNumPyData AnalysisData ScienceLLMsCommunication

About the role

  • We are seeking a talented and experienced AI/ML Engineer with a strong background in data science, generative AI, and agentics.

Responsibilities

  • Collaborate with cross functional teams to gather requirements and translate them into technical specifications.
  • Optimize and fine tune models for performance and scalability.
  • Document processes, methodologies, and results to ensure knowledge sharing within the team.

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • 5 7 years of experience in AI/ML engineering or a related role.
  • Excellent communication skills and the ability to work effectively in a team.
  • This role requires a deep understanding of AI/ML concepts and the ability to work collaboratively in a fast paced environment.

Skills

  • Strong expertise in TensorFlow, Keras and its ecosystem.
  • Proficient in Python and relevant libraries (e.g., NumPy, Pandas, Scikit learn).
  • Solid understanding of machine learning algorithms and techniques, including supervised and unsupervised learning.
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Familiarity with cloud platforms (e.g., Google Cloud, AWS) for deploying machine learning models.

Compensation

  • $140k-$145k

Benefits

  • Design, develop, and implement machine learning models using TensorFlow to solve complex business problems.
  • Conduct data analysis and preprocessing to ensure high quality input for machine learning algorithms.
  • Mentor junior team members and contribute to a culture of continuous learning and improvement.

This listing is sourced directly from Tech Mahindra (Americas) Inc.'s careers page and normalized into a canonical job model.