Software Engineer II

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Software Engineering

Software Engineer II on the Commerce – Platforms, Data, and Experiences (PDX) team, focusing on data strategy, scalable data platforms, and ML-driven insights. The role involves data engineering, data processing, and machine learning to solve business problems, design experiments, build predictive models, and develop scalable solutions. Responsibilities include designing analytics solutions with ML models, ensuring operability and scalability, conducting data analysis and feature engineering, leading experimentation, and building solutions on LLM models.

What you'd actually do

  1. Design and implement advanced analytics solutions to support commerce data platform initiatives including analytics based on Machine Learning Models. Design skill should include scale, extensibility, performance, re-training for the ML models.
  2. Partner with engineering and product teams to define data requirements and ensure high-quality data pipelines.
  3. Conduct exploratory data analysis, feature engineering, and model evaluation using structured and unstructured datasets.
  4. Ensure the models built are operable, scalable, extensible and performant.
  5. Develop dashboards, visualizations, and storytelling artifacts to communicate insights to stakeholders.
  6. Lead experimentation efforts to evaluate new features, forecasting, data quality and anomaly detection systems.
  7. Build extensible solutions on LLM models to improve productivity of engineers across the commerce organization.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice to have

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field.
  • 2+ years of experience in data science, analytics, or applied machine learning.
  • Proficiency in Python, SQL, and ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
  • Experience with cloud platforms (Azure preferred) and big data technologies.
  • Understanding of statistical modeling, predictive analytics, and experimentation design.
  • Excellent communication and stakeholder management skills.
  • Demonstrated experience leveraging AI tools and technologies to enhance engineering effectiveness, coupled with a strong curiosity and commitment to continuous learning in the field of Artificial Intelligence.

What the JD emphasized

  • advanced analytics solutions
  • Machine Learning Models
  • scale, extensibility, performance, re-training for the ML models
  • operable, scalable, extensible and performant
  • LLM models

Other signals

  • ML driven insights
  • build predictive models
  • LLM models