Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Design and build models and ML pipelines for user and conversation understanding in Copilot with an accent on natural language tasks like intent detection, topic classification, and summarization. Focus on developing transformer-based models, scalable pipelines with Spark and Azure ML, and rigorous experimentation to improve product metrics.

Location: Redmond, United States

Salary: USD $119,800 – $234,700 per year (USD $158,400 – $258,000 in San Francisco Bay area and New York City)

Company

hirify.global AI (MAI) building Copilot, the personal AI assistant to make AI accessible to all.

What you will do

• Design, train, evaluate, and deploy ML models for NLP tasks including intent detection, topic classification, conversation summarization, and user personas.
• Architect scalable training and inference pipelines using Spark, Databricks, Azure ML, and modern frameworks.
• Develop and fine-tune transformer-based models, text encoders, embedding pipelines, and vector databases for semantic search.
• Drive offline and online experimentation to measure quality, iterate architectures, and boost product metrics.
• Collaborate with data engineers, scientists, and product teams to ship features aligned with goals.
• Monitor production performance, diagnose issues, and contribute to strategic improvements and mentoring.

Requirements

• Bachelor’s in Statistics, Computer Science, or related AND 4+ years experience in statistics, predictive analytics, or research; OR Master’s AND 3+ years; OR Doctorate AND 1+ year (or equivalent).
• Experience across full ML lifecycle: data preparation, training, evaluation, deployment.
• Proficiency in Python and ML frameworks like PyTorch or Hugging Face Transformers.
• Experience with data platforms (Spark, Databricks, Azure ML) and end-to-end pipelines.

Nice to have

• Master’s/Doctorate with 6+/3+ years experience.
• Proven NLP with transformers for classification, encoding, summarization, semantic search.
• Text embeddings, vector DBs, RAG; distributed training, model optimization at scale.
• Search ranking, relevance modeling, information retrieval.

Culture & Benefits

• Growth mindset, innovation, collaboration with values of respect, integrity, accountability.
• Inclusive culture where everyone can thrive.
• Benefits and other compensation available; see corporate pay info.