AIML Engineer

Job Title: AI/ML Engineer
Location: Frisco TX/ Atlanta GA/ Bellevue WA (Onsite from Day 1) (Need Only Locals)
Looking for W2 No C2C

Job Description:

• We are seeking an AI/ML Engineer to build the intelligent systems that power identity resolution and data accessibility within our Customer Data Platform (CDP) - the authoritative source of truth for customer data across the entire US adult population.
• This role focuses on developing machine learning pipelines that deduplicate link and resolve customer identities across disparate data sources - the core capability that transforms raw data into trusted unified customer profiles. You will also contribute to LLM-based solutions that enable natural language querying of CDP data making the platform accessible to business users across the organization.
• You will work on both classical ML techniques and modern LLM-based approaches to ensure that every customer identity in CDP is accurately resolved every profile is trustworthy and every user can access the data they need.

Job Responsibilities:

• Develop and deploy entity resolution models to match and deduplicate customer records across multiple systems - directly impacting the accuracy of CDP as the source of truth
• Implement probabilistic matching techniques (e.g. Fellegi-Sunter) and ML models (gradient boosting neural classifiers) for record linkage across the US adult population
• Build candidate blocking pipelines using phonetic algorithms (Soundex Double Metaphone) token similarity and LSH to handle billions of potential match pairs efficiently
• Apply fuzzy matching techniques (Levenshtein Jaro-Winkler Jaccard) for customer attributes such as name address phone and identifiers
• Develop clustering algorithms (DBSCAN hierarchical clustering) to create unified golden customer profiles that serve as the authoritative representation of each individual
• Build embedding-based similarity systems using Sentence-BERT or transformer-based models for semantic matching
• Implement ANN/KNN retrieval systems (FAISS Annoy) for large-scale entity matching across population-scale datasets

Job Responsibilities - AI/LLM:

• Use LLMs (e.g. GPT Claude) for classification and disambiguation of entity matches improving resolution accuracy where traditional methods fall short
• Build and support RAG pipelines to enrich customer profiles with contextual data from unstructured sources
• Perform prompt engineering and evaluation for structured data extraction from unstructured inputs feeding into CDP
• Contribute to NLQ-to-SQL systems enabling business users to query CDP data using natural language - making the authoritative source of truth accessible to non-technical stakeholders
• Support integration with vector databases (e.g. Pinecone PGVector Qdrant) for semantic search across customer data

Education and Work Experience:

• Bachelors or masters degree in computer science Data Science or related field
• 3 years of experience in ML/AI engineering
• At least 1 year of experience in entity resolution record linkage or deduplication - ideally at scale

Technical Skills:

• Programming: Python (required)
• Libraries: scikit-learn HuggingFace Transformers RapidFuzz jellyfish
• Experience with LLM APIs (OpenAI Anthropic) and prompt pipelines
• Strong SQL skills and experience with Spark or Dask for distributed processing
• Familiarity with vector databases and embedding-based retrieval
• Experience with ML lifecycle tools (MLflow or similar)
• Understanding of data quality metrics and how identity resolution impacts downstream trust

Knowledge Skills and Abilities:

• Strong understanding of ML fundamentals and similarity matching techniques applied to customer identity
• Ability to work with large messy real-world datasets spanning hundreds of millions of records
• Understanding of precision/recall tradeoffs in identity resolution and their impact on data trust
• Good problem-solving and analytical skills
• Ability to collaborate with data engineering platform and business teams to deliver accurate customer profiles
  

Best Regards:

Tanuja P
Phone: 1-
Email: