Data Scientist / ML Engineer / ML Architect

About

We are hiring multiple highly skilled Data Scientists, ML Engineers, and ML Architects to work on large-scale AI/ML initiatives focused on NLP, search relevance, ranking systems, recommendation engines, and model optimization.

This is a fast-moving opportunity for hands-on engineers who can design, build, evaluate, and optimize production-grade machine learning systems at scale.

Key Responsibilities

• Build and optimize NLP pipelines for search, recommendations, and semantic understanding
• Develop ML models for intent classification, entity recognition, ranking, and relevance
• Train and deploy transformer-based models using HuggingFace, BERT, Sentence-BERT, and PyTorch
• Design Learning-to-Rank (LTR) and recommendation systems using LambdaMART, XGBoost, CatBoost, and LightGBM
• Develop semantic search and vector retrieval systems using FAISS/HNSW
• Build scalable data pipelines using PySpark, Spark, Dataflow, and BigQuery
• Perform offline and online model evaluation using nDCG, MRR, MAP@K, and A/B testing methodologies
• Optimize scoring pipelines, feature engineering workflows, and model deployment infrastructure
• Collaborate cross-functionally with product, engineering, and business stakeholders

Required Skills

• Strong Python programming experience
• Hands-on experience with NLP and transformer-based architectures
• Experience with HuggingFace, spaCy, BERT, FastText, Sentence-BERT, or semantic matching systems
• Experience with ML frameworks such as PyTorch or TensorFlow
• Experience with ranking/relevance models and recommendation systems
• Strong data engineering experience using PySpark/Spark/Dataflow
• Experience with MLOps, model deployment, training pipelines, and artifact versioning
• Familiarity with GCP, BigQuery, Azure ML, or cloud-based ML platforms
• Strong understanding of model evaluation metrics and experimentation frameworks

Preferred Qualifications

• Experience working on large-scale retail, ecommerce, marketplace, search, or personalization platforms
• Experience building production-grade ML systems at enterprise scale
• Experience with feature stores such as Feast or Tecton
• Strong communication and stakeholder management skills
• Architect-level candidates should be highly hands-on and capable of leading technical direction

Salary

The national base pay range below is a good-faith estimate of what our client may pay for new hires. Actual pay may vary based on Client's assessment of the candidates knowledge, skills, abilities (KSAs), related experience, education, certifications and ability to meet required minimum job qualifications. Other factors impacting pay include prevailing wages in the work location and internal equity. $130,000 - $160,000