Design, train, and refine ML models (including deep learning and reinforcement learning approaches) to power new browser experiences. This includes creating training pipelines, performing data cleaning/feature engineering, and iterating on model architectures using large-scale datasets. Stay up-to-date with the latest research trends in machine learning and AI. Bring in new ideas from academia/industry and evaluate their potential in the scope of work. Mentor and share knowledge with team member…
Responsibilities
Develop and integrate AI/ML features: Collaborate with product and engineering teams to identify opportunities for AI-driven improvements in Edge and design features that improve user experience. Conduct offline experiments and online A/B tests to generate insights and evaluate model performance and feature impact. Analyze results and metrics to drive iterative improvements and deliver meaningful user and business value. Build and maintain end-to-end data pipelines and tools for development and inference (from data collection through model deployment). Work with engineering to integrate models into production, monitor their performance, and optimize for efficiency and scale.
Required Qualifications
Bachelor's degree in computer science, statistics, engineering, or a related field (machine learning, data science); OR a Master's degree in a related field AND 4+ years of experience. Solid understanding of core machine learning concepts (e.g., predictive modeling, classification, optimization) and hands-on experience developing models from scratch to production. Proficiency with ML frameworks such as PyTorch or TensorFlow is highly desirable. Strong coding skills in Python (pandas, PyTorch/TensorFlow, scikit-learn, etc.). Experience writing efficient code for data processing and model inference in a production environment. Proven ability to analyze and derive insights from large, complex datasets. Experience with data tools and pipelines (SQL, Spark/Hadoop, or Azure Machine Learning pipelines) for handling “big data” is a plus. Excellent analytical and problem-solving skills with a track record of driving improvements through experimentation and data-driven decision making. Ability to design sound experiments and interpret results correctly (statistical rigor, significance testing, etc.). Strong communication and teamwork skills. Ability to effectively collaborate in a multidisciplinary team, synthesize complex ideas, and communicate technical results to non-experts in clear, concise ways. Hands-on experience with A/B testing and analysis of user engagement metrics. Ability to work closely with product teams to formulate hypotheses and interpret experiment outcomes to inform product decisions. Experience with deep learning techniques (e.g. neural networks, transformers) and/or reinforcement learning in an applied setting. Familiarity with modern ML model development, tuning, and evaluation practices at scale. A record of research innovation as evidenced by publications in top AI/ML conferences or filed patents is a strong plus (demonstrates ability to contribute new knowledge to the field). Familiarity with web/browser technologies or prior experience in consumer-facing product teams. Understanding of how browser features work and how users interact with them can help in designing more effective ML solutions (e.g. knowledge of user behavior patterns in web browsing).
Original Posting
This role is sourced from Microsoft. Apply on Microsoft careers page