Machine Learning Engineer

Overview

On Site
$60,000 - $80,000
Full Time

Skills

Artificial Intelligence
Kubernetes
Python
Continuous Integration
Data Extraction
Machine Learning (ML)
Docker
Extraction
Microsoft Azure
Collaboration
TensorFlow
PyTorch

Job Details

Machine Learning Engineer

Irving, TX (Day 1 Onsite)

Visa: GCEAD And USC

Responsibilities

  • Develop and optimize embedding pipelines for image and text similarity (e.g., CLIP, SigLIP, Sentence Transformers).
  • Implement vector search and retrieval using FAISS, Pinecone, or pgvector.
  • Build feature extraction pipelines (OCR + NER + numeric parsers) to detect schema-defined attributes.
  • Design and validate a feature comparison engine to detect missing or low-confidence values.
  • Integrate conversational AI agents with slot-filling logic to request missing details from users.
  • Apply server-side validation for numeric, categorical, and free-text inputs.
  • Track experiments using MLflow / W&B and evaluate with metrics like Recall@k, MRR, F1.
  • Deploy retrieval and conversational services on Kubernetes / App Services with CI/CD pipelines.
  • Collaborate cross-functionally with engineers and product teams to refine schema and conversational UX.

Qualifications

  • Strong knowledge of embeddings and retrieval models for multi-modal data.
  • Experience with OCR + NER pipelines for structured data extraction.
  • Proficiency in vector databases (FAISS, Pinecone, pgvector, Azure AI Search).
  • Familiarity with LLM integration for conversational AI (tooling, slot-filling, schema control).
  • Strong Python and PyTorch/TensorFlow skills.
  • Hands-on experience with containerized ML services (Docker, Kubernetes).

Preferred

  • Experience combining image + text embeddings into unified retrieval pipelines.
  • Knowledge of schema-driven conversational AI design.
  • Familiarity with monitoring & drift detection tools (Evidently, Prometheus).

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