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Founding Machine Learning Engineer Jobs in Texas

Q2 India

Machine Learning Engineer

Austin, TX · On-site

$100 - $130/hr

Machine Learning Engineer page is loaded## Machine Learning Engineerlocations: Austin, TXtime type: Full timeposted on: Posted Yesterdayjob requisition id: REQ-12438# **As passionate about our people ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Avride develops autonomous vehicle and delivery robot technology, and they are seeking an experienced Machine Learning Engineer to enhance their autonomous systems. The role involves developing and ...

AtOrchard LLC

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard: @Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical ...

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · 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 ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Confie

Machine Learning Engineer

Addison, TX · 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 ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

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 ...

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Founding Machine Learning Engineer information

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.

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.

Are founding machine learning engineers still in demand?

Founding machine learning engineers remain in high demand as companies seek to develop AI-driven products and services. They often require strong skills in deep learning, data modeling, and proficiency with tools like TensorFlow or PyTorch, with demand driven by growth in AI applications across industries.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $100,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses may also be part of the compensation package, especially in startup environments where they play a significant role in total earnings.

What are popular job titles related to Founding Machine Learning Engineer jobs in Texas?

For Founding Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Founding Machine Learning Engineer jobs in Texas look for?

The top searched job categories for Founding Machine Learning Engineer jobs in Texas are:

What cities in Texas are hiring for Founding Machine Learning Engineer jobs?

Cities in Texas with the most Founding Machine Learning Engineer job openings:

Founding Machine Learning Engineer jobs near you
Infographic showing various Founding Machine Learning Engineer job openings in Texas as of August 2026, with employment types broken down into 33% Internship, and 67% Full Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Rivago infotech inc

Dallas, TX • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Role: Machine Learning Engineer - Fraud Detection

Location: Dallas, TX (100% Onsite)

 

Role Summary

We are looking for a Machine Learning Engineer to build and support production-grade fraud detection solutions. The role focuses on real-time inference, feature engineering, APIs, graph-based fraud detection, and production deployment support.

 

Key Skills

  • Machine Learning Engineering and Real-Time Inference
  • Python, APIs, and Microservices
  • Google Cloud Platform and Databricks
  • Neo4j / Graph Databases and Feature Stores
  • Data Pipelines and Feature Engineering
  • MLOps, Monitoring, and Production Support
  • Agentic AI Architecture (good to have)

 

Responsibilities

  • Build and deploy fraud detection services for production use.
  • Develop low-latency inference solutions with a target of less than 250 ms.
  • Design feature engineering pipelines for ML use cases.
  • Integrate ML models with REST APIs and microservices.
  • Support graph-based fraud detection using Neo4j.
  • Improve scoring performance, reliability, and scalability.
  • Work with MLOps teams for releases, monitoring, and production support.
  • Support data quality, governance, and operational activities.

 

Required Qualifications

  • Hands-on experience in Python and ML model deployment.
  • Experience with APIs, microservices, and production ML systems.
  • Knowledge of data pipelines, data engineering, and feature stores.
  • Exposure to Google Cloud Platform, Databricks, Data Lake, or Data Warehouse platforms.
  • Basic understanding of MLOps, monitoring, and release support.
  • Good communication and problem-solving skills.

 

Nice to Have

  • Fraud detection, risk analytics, or scoring model experience.
  • Experience with Neo4j or graph-based ML solutions.
  • Understanding of Agentic AI architecture.

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