Senior Software Engineer, Ai/ml, AI Garage

Google Google · Big Tech · Hyderabad, Telangana, India

Senior Software Engineer, AI/ML role focused on leading the design, development, and deployment of AI-powered solutions for HR processes within Google's global workforce. The role involves technical leadership, architecting scalable AI/ML systems, driving algorithm development, owning the MLOps lifecycle, and collaborating with cross-functional partners to translate business needs into AI-driven roadmaps.

What you'd actually do

  1. Lead the technical design and architecture of complex, scalable AI/ML systems and infrastructure within the HR engineering domain, ensure high reliability, performance, and long-term sustainability.
  2. Drive the development of advanced algorithms for HR applications like talent acquisition and engagement using Python and Google’s internal frameworks, including TensorFlow and JAX, to solve tests.
  3. Architect data pipelines using Google’s infrastructure (e.g., Beam, Dataflow) for large-scale data ingestion, cleaning, and complex feature engineering, while leading root cause analysis for system troubleshooting.
  4. Own the full MLOps lifecycle, including deployment, monitoring, and optimization of production models, while establishing team-wide best practices for software development processes and high-quality code.
  5. Collaborate with cross-functional partners to translate business needs into technical roadmaps, provide mentorship to engineers and drive the strategic adoption of emerging AI technologies across the organization.

Skills

Required

  • software development
  • software design and architecture
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • model deployment
  • model evaluation
  • data processing
  • debugging

Nice to have

  • Master’s degree or PhD in Computer Science or a related field with a focus on Artificial Intelligence (AI) or Machine Learning (ML)
  • large-scale AI/ML applications and complex models
  • MLOps
  • production model monitoring, maintenance, and lifecycle management
  • leading and mentoring engineers
  • scalable data pipelines
  • BigQuery
  • Beam
  • Dataflow
  • Google Cloud Platform
  • Python
  • TensorFlow
  • JAX
  • Scikit-learn
  • statistical modeling

What the JD emphasized

  • AI/ML systems
  • advanced algorithms
  • MLOps lifecycle
  • production models
  • AI technologies

Other signals

  • AI/ML to optimize HR processes
  • AI-powered solutions that significantly impact Google's employees
  • AI applications
  • AI/ML systems
  • advanced algorithms for HR applications
  • MLOps lifecycle
  • production models
  • emerging AI technologies