Bangalore, Karnataka, India
Information Technology
Full-Time
Google
Overview
Minimum qualifications:
Responsibilities
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 5 years of experience in developing machine learning models such as recommender systems, pricing optimization, user modeling, or computational advertising.
- Experience architecting and deploying ML systems that function efficiently at a massive scale.
- Experience mentoring and leading engineers on technical projects.
- Understanding of large-scale data processing frameworks such as SQL, Spark or MapReduce, Python for efficient data querying and analysis.
- Excellent communication skills with the ability to convey the team's technical goal effectively to executive leadership and cross-functional stakeholders.
Responsibilities
- Establish and lead the long-term technical goal for ML powered personalization, pricing and recommendation systems that scale to billions of users.
- Design, develop and scale production-grade ML systems with strong emphasis on performance, reliability, debuggability and model explainability.
- Serve as a technical pillar for the team by mentoring engineers, fostering their growth, providing design guidance and cultivating a culture of engineering excellence.
- Identify high-impact machine learning applications to drive user growth, engagement, and business, while leading complex modeling initiatives from exploring novel algorithmic approaches for offer optimization to developing models for new product tiers.
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