Description We are seeking a Machine Learning Engineer II to join a large-scale technology organization focused on building next-generation AI/ ML capabilities across search, browse, personalization, voice, NLP, and advanced automation platforms. This global team focuses on developing cutting-edge products leveraging large language models (LLMs), GPT-based systems, and innovative AI-driven tools. This role sits within a group that partners closely with SDET and tooling teams to design, validate, and enhance ML models that support intelligent automation frameworks and high-impact engineering initiatives.
As a Machine Learning Engineer II, you will:
- Design, build, and validate machine learning models used to support and enhance internal automation tools.
- Develop ML models that assist in validating and improving tools created by engineering and tooling teams.
- Enhance existing models to strengthen AI/ML automation initiatives -especially those involving speech, NLP, and voice-driven data.
- Implement prompt-based interaction workflows with large language models.
- Collaborate extensively with cross-functional engineering squads, SDET organizations, and automation tooling teams.
- Support research and exploration of new ML models across multiple domains including NLP, Computer Vision, and emerging AI research areas.
- Contribute to the development of automated frameworks and proof-of-concept AI/ML solutions.
- Ensure high product quality and accuracy, particularly within LLM-based systems.
Responsibilities:- Lead the design and development of scalable ML-driven systems that drive intelligent automation.
- Own end-to-end workflows including data engineering, model development, training, evaluation, and deployment.
- Integrate ML and NLP components into robust, high-performing software solutions.
- Collaborate with engineering, SDET, product, and automation teams to align technical approaches with business goals.
- Ensure reliability, model quality, and long-term maintainability of ML systems.
- Mentor SDET teams on ML best practices, data workflows, and model evaluation techniques.
- Explore emerging ML technologies and contribute findings toward future automation initiatives.
Requirements Minimum Qualifications:- 4+ years total engineering experience, including 1+ years hands-on experience building or training ML models.
- Strong experience with ML model development, validation, and enhancement.
- Familiarity with LLMs and practical experience implementing prompt based interactions.
- Ability to evaluate and test LLMs using other LLM-based frameworks.
- A strong quality-focused mindset - ensuring accuracy, reliability, and sound model behavior.
- Experience with NLP, speech data, or automation-focused ML workflows.
- Proven ability to collaborate effectively with distributed engineering teams.
- Experience designing scalable software systems incorporating ML/AI components.
Preferred Qualifications:- Experience working in environments with large distributed engineering teams.
- Prior exposure to Computer Vision, deep learning frameworks, or model evaluation methodologies.
- Demonstrated ability to contribute to research-grade or PoC-level ML projects.
- Knowledge of modern tooling used across AI/ML pipelines and data engineering.
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