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# Job Title: Senior Machine Learning Engineer (Generative AI & Cloud Platforms)

- **Company:** Learn Beyond Consulting LLC
- **Location:** Atlanta, GA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Algorithm Design, Automation of Tests, Big Data, BigQuery, Network Analysis, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Graph Database, Python (Programming Language), Machine Learning, NoSQL, Performance Tuning, Tensorflow, Azure Machine Learning, Search Technologies, Software Construction, Software Engineering, SQL Databases, Unstructured Data, Data Logging, Scripting, Google Cloud, Pytorch, Large Language Models, Generative AI, Core Api, Pandas, Build Management, Containerization, Scikit Learn, Production Code, Machine Learning Operations, Virtual Agents, Software Version Control, Data Pipelines, Programming Languages
- **Published:** September 28, 2026
- **Apply:** https://www.dice.com/job-detail/080ad17a-fd34-4b86-957e-3ce536018353

## About the Role

* Experience: 5+ years of professional experience in Machine Learning Engineering, AI Engineering, Software Engineering, or a related field, with a proven track record of deploying production-grade AI solutions.
 * GenAI & LLMs: Hands-on experience building Agentic AI applications, LLM-powered solutions, RAG systems, and intelligent automation workflows.
 * Data & Knowledge Layers: Strong experience with knowledge graphs, graph engineering, network analysis, semantic search, and combining structured/unstructured data.
 * Core Languages & Frameworks: Proficiency in Python and modern AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn, Pandas).
 * Cloud & MLOps: Experience with cloud-native AI/ML platforms, preferably Google Cloud Platform (Vertex AI, BigQuery, BigQuery ML), containerization, and vector databases.
 * Software Engineering Best Practices: Solid understanding of CI/CD, version control, automated testing, security, and performance optimization across large-scale data systems (SQL, NoSQL).
 * Education: Minimum high school diploma and/or GED (relevant technical degree preferred)., * Global Perspective & Managing Ambiguity
 * Nimble Learning & Self-Development
 * Strong Collaboration & Interpersonal Savvy
 * Communicates Effectively
 * Cultivates Innovation & Drives Results
 * Situational Adaptability

## Description

We are looking for a collaborative, hands-on Senior Machine Learning Engineer to join our product team. In this role, you will contribute to the software design, algorithm design, and overall product lifecycle for innovative, user-centric AI solutions.

Our engineering process is highly collaborative and agile. You will pair daily with cross-functional team members, review code based on best practices, and build scalable machine learning systems that drive real business value. If you thrive in a fast-paced, innovative environment and have a passion for production-grade GenAI, cloud-native architecture, and modern MLOps, we want to hear from you., <>Delivery & Execution (70%)

 * Collaborate and pair daily with product team members (UX, engineering, and product management) to design and build secure, reliable, scalable machine learning solutions.
 * Architect and implement cutting-edge AI/ML algorithms, Agentic AI applications, and Retrieval-Augmented Generation (RAG) workflows.
 * Design and develop enterprise knowledge layers utilizing knowledge graphs, semantic search, and vector databases.
 * Write clean, maintainable code and automated scripts for infrastructure, monitoring services, and test cases, including "destructive testing" to ensure production resiliency.
 * Create meaningful dashboards, logging, and alerting systems to proactively track and address issues.
 * Document and review code to ensure adherence to high quality, security, and change control standards.

<>Support & Enablement (20%)

 * Provide robust application support for software running in production, monitoring Service Level Objectives (SLOs) and prediction quality.
 * Proactively evaluate the performance and capacity of production code, infrastructure, data pipelines, and message processing.
 * Field technical questions from product and support teams while driving cross-team collaboration.

<>Learning & Continuous Improvement (10%)

 * Participate actively in communities of practice around modern software design, machine learning, and core development practices.
 * Proactively explore new technologies, frameworks, and industry best practices.