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# Data Scientist

- **Company:** Dialog LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Big Data, Continuous Integration, Software Debugging, Distributed Data Store, Python (Programming Language), Machine Learning, Pytorch, Large Language Models, Deep Learning, Backend, Machine Learning Operations, Virtual Agents, Microservices
- **Published:** August 26, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pfdyie3x24

## About the Role

* 5+ years of hands-on industry experience as a Machine Learning Engineer or Data Scientist - Mandatory
 * Proven track record of taking ML / Deep Learning models fully into Production with ongoing operational ownership (monitoring, drift mitigation, retraining, debugging; prototype-only experience is not sufficient) - Mandatory
 * Deep proficiency in Python, with proven experience authoring tested, enterprise-grade production modules and/or owning microservices under CI/CD - Mandatory
 * Extensive hands-on experience building and training custom architectures using PyTorch and deploying them to production - Mandatory
 * Solid hands-on experience working within Big Data Platforms & distributed data infrastructures - Mandatory
 * Direct ownership of Production Engineering workflows / MLOps pipelines - Mandatory
 * Hands-on experience deploying LLMs or Agentic AI applications in Production (including evaluations, guardrails, and latency/cost tuning) - Significant Advantage
 * Practical experience working with Noisy, Unstructured, or Weakly-Labelled Data / Time-Series Telemetry - Significant Advantage

## Description

* Serving as a Senior Machine Learning / AI Production Engineer, taking full end-to-end ownership of the ML lifecycle-from exploratory data analysis and custom architecture modeling to high-throughput production deployment and ongoing operations.
 * Processing and modeling billions of noisy, high-velocity, real-time vehicular telemetry data points to build robust predictive maintenance and behavioral models.
 * Designing, training, and optimizing custom deep learning architectures in PyTorch, transitioning complex prototypes into scalable, testable production services.
 * Taking complete operational ownership of models in Production, including continuous monitoring, automated retraining pipelines, drift detection, and live debugging under robust CI/CD frameworks.
 * Developing and deploying production-grade LLM and Agentic AI applications, implementing evaluation frameworks (Evals), guardrails, latency optimization, and cost-governance mechanisms.
 * Collaborating cross-functionally with Big Data Engineers, Backend Architects, and Automotive Product domain experts.


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