Data Scientist / ML Engineer / ML Architect

Data Scientist / ML Engineer / ML Architect📍 Bay Area, CA (Hybrid/Onsite Preferred)💰 ContractWe 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 ResponsibilitiesBuild and optimize NLP pipelines for search, recommendations, and semantic understandingDevelop ML models for intent classification, entity recognition, ranking, and relevanceTrain and deploy transformer-based models using HuggingFace, BERT, Sentence-BERT, and PyTorchDesign Learning-to-Rank (LTR) and recommendation systems using LambdaMART, XGBoost, CatBoost, and LightGBMDevelop semantic search and vector retrieval systems using FAISS/HNSWBuild scalable data pipelines using PySpark, Spark, Dataflow, and BigQueryPerform offline and online model evaluation using nDCG, MRR, MAP@K, and A/B testing methodologiesOptimize scoring pipelines, feature engineering workflows, and model deployment infrastructureCollaborate cross-functionally with product, engineering, and business stakeholdersRequired SkillsStrong Python programming experienceHands-on experience with NLP and transformer-based architecturesExperience with HuggingFace, spaCy, BERT, FastText, Sentence-BERT, or semantic matching systemsExperience with ML frameworks such as PyTorch or TensorFlowExperience with ranking/relevance models and recommendation systemsStrong data engineering experience using PySpark/Spark/DataflowExperience with MLOps, model deployment, training pipelines, and artifact versioningFamiliarity with GCP, BigQuery, Azure ML, or cloud-based ML platformsStrong understanding of model evaluation metrics and experimentation frameworksPreferred QualificationsExperience working on large-scale retail, ecommerce, marketplace, search, or personalization platformsExperience building production-grade ML systems at enterprise scaleExperience with feature stores such as Feast or TectonStrong communication and stakeholder management skillsArchitect-level candidates should be highly hands-on and capable of leading technical directionThe 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