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MLOps Engineer

MetaSense, Inc.Hollywood, FL🇺🇸United StatesPosted 19 Aug 2026

Why This Role Stands Out

This hybrid MLOps Engineer role at MetaSense, Inc. offers a fantastic opportunity to leverage your extensive machine learning and Python expertise in building and deploying large-scale recommendation engines and personalization solutions. You'll thrive if you have a proven track record in technical leadership, experience with Databricks, MLflow, and major ML frameworks, and are adept at managing the full model lifecycle. Apply today to contribute to impactful projects and gain valuable experience in a dynamic environment.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Job Title: MLOps Engineer 
Location: Hollywood, FL
Employment Type: 6-month Contract
Tax term: W2-contract only 
  
 Required Skills:
  • 8+ years of Machine Learning Engineering or applied AI experience.
  • 3+ years in Lead, Principal, or senior technical leadership roles.
  • Strong hands-on Python development for production-grade machine learning solutions.
  • Advanced experience with Databricks, MLflow, and distributed machine learning workloads.
  • Expertise with TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.
  • Proven experience building and deploying large-scale recommendation engines.
  • Strong experience developing customer personalization and customer intelligence solutions.
  • Experience with customer segmentation, churn prediction, and customer value models.
  • Strong understanding of Customer 360 platforms and unified customer data.
  • Experience using identity graphs to improve customer matching and prediction accuracy.
  • Strong feature engineering, model evaluation, validation, and lifecycle management experience.
  • Experience designing scalable batch and real-time inference architectures.
  • Proven experience deploying, monitoring, and retraining machine learning models in production.
  • Experience partnering with Data Engineering teams to create ML-ready datasets.
  • Strong architecture experience across Data Science, Engineering, and MLOps platforms.
  • Experience leading technical design reviews and establishing enterprise ML standards.
  • Strong mentoring, stakeholder communication, and cross-functional technical leadership skills.
Preferred Skills:
  • Experience with Snowflake and integrated Databricks data environments.
  • Experience building GenAI, LLM-powered, or agentic AI applications.
  • Experience developing domain-specific AI agents and intelligent assistants.
  • Knowledge of MLOps, feature stores, model serving, and automated retraining.
  • Experience with real-time recommendation and streaming personalization platforms
 

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