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Founding Machine Learning Engineer Jobs in Dallas, TX

Machine Learning Engineer

Frisco, TX ยท On-site

$140 - $190/hr

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Machine Learning Engineer

Addison, TX ยท On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

A Machine Learning Engineer helps our learners discover content that is relevant to their interests and goals, providing them with experiences tailored just to their needs, and ensure they are ...

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Machine Learning Engineer

Plano, TX ยท On-site

$120 - $150/hr

Overview Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in ...

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

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Founding Machine Learning Engineer information

See Dallas, TX salary details

$31.2K

$127.4K

$191.4K

How much do founding machine learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for founding machine learning engineer in Dallas, TX is $127,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 per year, depending on experience, location, and employer.

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $120,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses are also common components of compensation, especially in startup environments where they play a significant role in total earnings.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What are the key skills and qualifications needed to thrive as a founding machine learning engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.
What cities near Dallas, TX are hiring for Founding Machine Learning Engineer jobs? Cities near Dallas, TX with the most Founding Machine Learning Engineer job openings:

Machine Learning Engineer

UNAVAILABLE

Frisco, TX โ€ข On-site

$140 - $190/hr

Other

Posted 5 days ago


Job description

Overview

Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will design, develop, and deploy state-of-the-art computer vision and language models that power scalable, real-world solutions. Youโ€™ll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.

As part of our AI team, youโ€™ll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings handsโ€‘on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.

Responsibilities
  • Fineโ€‘tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
  • Develop visionโ€‘language models and Mixture of Experts architectures, from experimental design through production deployment.
  • Architect Retrievalโ€‘Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
  • Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
  • Contribute to our machine learning repositories and optimize models for performance, scalability, and realโ€‘time inference across edge and cloud environments.
  • Drive performance optimization and scalability of ML systems across edge and cloud environments.
  • Collaborate with crossโ€‘functional teams to integrate computer vision solutions into endโ€‘toโ€‘end products, translating research outcomes into measurable platform impact.

This list of responsibilities might not cover everything you'll end up doing.

Qualifications
  • 5+ years of handsโ€‘on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
  • Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
  • Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
  • Experience building and deploying LLM-based systems and Retrievalโ€‘Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
  • Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.
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