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# ML Engineer

- **Company:** Catalyst
- **Location:** Fort Worth, TX, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Computer Programming, Data Transformation, Monitoring of Systems, Python (Programming Language), PostgreSQL, Machine Learning, Redis, OpenAI, Tensorflow, Software Deployment, TypeScript, Unstructured Data, Cloud Platform System, Feature Engineering, Data Ingestion, Pytorch, Large Language Models, Fastapi, Real-time Inference, Information Technology, LiteLLM, Machine Learning Operations, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/ml-engineer-fort-worth-tx--32c2ec7d-90ea-4e28-8303-86f9c35fa312

## About the Role

Startup, Analysis Skills, Funding, Customer Relations, Field Sales, Artificial Intelligence (AI), Coaching, Customer Experience, Sales Closing Skills, Data Science, * Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

 * 1-6 years of professional experience in ML engineering.
 * Strong programming skills in Python (TypeScript experience is a plus).
 * Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 * Familiarity with cloud environments and infrastructure (preferably AWS).
 * Strong understanding of data pipeline design, real-time inference, and model monitoring.
 * Excellent communication skills with the ability to engage directly with customers and stakeholders.

Core Experience

 * Proven experience building and deploying ML models into production environments.
 * Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
 * Experience with audio-focused ML projects or similar domains involving unstructured data.
 * Proficiency in building scalable data pipelines for model training and evaluation.
 * Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
 * Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.

## Description

* Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
 * Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
 * Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
 * Build agents capable of operating natively on real-world audio inputs.
 * Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
 * Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
 * Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
 * Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.