Data Scientist / ML Engineer / ML Architect

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

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

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