Machine Learning Developer (MLOps & AI Platforms)

Fuse3 Solutions; Broken Arrow (OK); On-site; USD 112,000 - 140,000; Full time

Job summary

Fuse3 Solutions seeks a Machine Learning Developer to bridge data science innovation with enterprise-grade software engineering. You will build the organization's MLOps framework and define best practices for moving models from experimentation to production.

As the first dedicated ML Development hire, you will shape the standards, patterns, and governance for AI delivery and partner with data scientists to productionize models in the Databricks ecosystem, driving enterprise-wide AI initiatives.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related discipline
• 3 to 5 years of experience building and deploying production machine learning or data-intensive applications
• Hands-on experience with Databricks MLflow and AutoML
• Strong Python development skills with production-quality code
• Strong SQL expertise and experience with Spark or distributed data processing technologies
• Experience creating and operating MLOps processes and deployment frameworks
• Knowledge of software engineering best practices including Git, testing methodologies, CI/CD, and design patterns
• Understanding of machine learning algorithms, model evaluation techniques, and tuning methodologies
• Proven ability to collaborate across technical and business teams

Responsibilities

• Create the organization's MLOps framework and define best practices for moving models from experimentation to production
• Build reusable machine learning deployment patterns and establish the team's 'golden path' for ML development
• Partner closely with data scientists to productionize models within the Databricks ecosystem
• Design and automate CI/CD pipelines for model training, testing, deployment, and promotion across environments
• Implement governance, lineage, versioning, and lifecycle management for machine learning assets
• Develop monitoring, observability, and reliability standards for production ML solutions
• Ensure model and feature quality through validation frameworks and automated controls
• Create technical documentation, reference architectures, and engineering playbooks
• Guide technical teams through code reviews and adoption of modern ML engineering practices
• Evaluate and introduce emerging AI technologies, including Generative AI, LLM-enabled workflows, and agentic development approaches

Skills

Python development

SQL

MLOps

Git

CI/CD

Data science collaboration

Education

Bachelor's degree

Tools

Databricks MLflow

AutoML

Spark

Unity Catalog

Job description

*No sponsorship or CDC candidates able to be considered*

Pay: $112k-$140k with 15% STI & 20% LTI. Location: Dallas

Build the Foundation for the Future of AI

What if you had the opportunity to be the architect behind an organization's machine learning future?

We are partnering with a highly respected, data-driven enterprise that is making a significant investment in AI, machine learning, and advanced analytics. As the first dedicated Machine Learning Developer on the team, you will have a rare opportunity to define the standards, platforms, and engineering practices that transform innovative data science experiments into scalable, reliable production solutions.

This is not a maintenance role. This is a chance to build the machine learning delivery framework from the ground up, influence enterprise-wide AI strategy, and establish the blueprint that future teams will follow.

If you are passionate about MLOps, production machine learning, automation, and emerging AI technologies, this role offers the visibility, ownership, and impact to help shape an organization’s next generation of intelligent solutions.

What You'll Do

As the Machine Learning Developer, you will serve as the bridge between data science innovation and enterprise-grade software engineering.

You will:

• Create the organization's MLOps framework and define best practices for moving models from experimentation to production
• Build reusable machine learning deployment patterns and establish the team's "golden path" for ML development
• Partner closely with data scientists to productionize models within the Databricks ecosystem
• Design and automate CI/CD pipelines for model training, testing, deployment, and promotion across environments
• Implement governance, lineage, versioning, and lifecycle management for machine learning assets
• Develop monitoring, observability, and reliability standards for production ML solutions
• Ensure model and feature quality through validation frameworks and automated controls
• Create technical documentation, reference architectures, and engineering playbooks
• Guide technical teams through code reviews and adoption of modern ML engineering practices
• Evaluate and introduce emerging AI technologies, including Generative AI, LLM-enabled workflows, and agentic development approaches

Why This Role Stands Out

Be the Builder

This is the organization's first dedicated ML Development hire. You'll set the standards, select the patterns, and help establish the future operating model for machine learning delivery.

Enterprise Impact

Your work will directly influence how AI solutions are developed, governed, deployed, and scaled across the business.

Modern Technology Stack

Work extensively with:

• Databricks
• MLflow
• AutoML
• Unity Catalog
• Model Serving
• Python
• SQL
• Spark
• CI/CD Platforms
• Cloud-Based Data and AI Technologies

Shape the Future of AI

Explore cutting-edge AI delivery approaches including large language models, retrieval-augmented generation, AI-assisted development, and emerging machine learning operations capabilities.

What We're Looking For

Required Experience

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related discipline
• 3 to 5 years of experience building and deploying production machine learning or data-intensive applications
• Hands-on experience with Databricks MLflow and AutoML
• Strong Python development skills with experience writing maintainable, production-quality code
• Strong SQL expertise and experience with Spark or distributed data processing technologies
• Experience creating and operating MLOps processes and deployment frameworks
• Knowledge of software engineering best practices including Git, testing methodologies, CI/CD, and design patterns
• Understanding of machine learning algorithms, model evaluation techniques, and tuning methodologies
• Proven ability to collaborate across technical and business teams

Preferred Experience

• Unity Catalog experience supporting governance and controlled model promotion
• Databricks certifications
• Advanced degree in a related field
• Experience with cloud platforms, containers, orchestration technologies, or infrastructure automation
• Exposure to LLM, GenAI, or RAG solutions
• Previous mentoring or technical leadership experience
• Self-directed work style with strong organizational skills

Who Will Thrive Here?

We're looking for someone who enjoys creating structure where none exists, building platforms that others depend on, and driving adoption of engineering excellence. The ideal candidate combines the mindset of a software engineer, the curiosity of a data scientist, and the vision of an AI innovator.

If you're excited about building the machine learning foundation that enables an organization to scale AI confidently and responsibly, we'd love to connect with you.