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Founding Machine Learning Engineer Jobs in Houston, TX

Senior AI Engineer - SFL Scientific

Houston, TX · On-site

$99K - $137K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Sr. ML Ops Engineer

Spring, TX

$96K - $132K/yr

... Engineers to identify and define requirements ... Design, develop, and support machine learning operations (MLOps) platforms and tools in support of ...

Principal Data Engineer

Houston, TX · On-site

$106K - $127K/yr

This position demands a blend of cloud data engineering, systems engineering, data integration, and machine learning systems knowledge to enhance GST's data capabilities, supporting advanced ...

AI ML Operations Engineer

Houston, TX · On-site

$66K - $89K/yr

They are seeking an experienced AI Machine Learning Operations Engineer to research, build, and design artificial intelligence systems that automate predictive models and design machine learning ...

AI Data Scientist - Enterprise AI

Spring, TX · On-site

$130K - $205K/yr

This role sits at the intersection of applied research, machine learning engineering, data science, and business transformation. The ideal candidate combines strong technical expertise in Large ...

Software Engineer in Data Science

Houston, TX · On-site

$109K - $131K/yr

The individual will work both with our data scientists and machine learning engineers but will also need to directly engage with the commercial teams (across trading, operations, support functions ...

Showing results 41-60

Founding Machine Learning Engineer information

See Houston, TX salary details

$30.1K

$123K

$184.8K

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

As of Jul 28, 2026, the average yearly pay for founding machine learning engineer in Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 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.

What engineer makes $500,000 a year?

A founding machine learning engineer at top tech companies or successful startups can earn $500,000 or more annually, often including base salary, bonuses, and equity. Such roles typically require advanced skills in deep learning, data modeling, and experience with large-scale systems, along with a strong track record of innovation and leadership.

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 is a founding ML engineer?

A founding machine learning engineer is a key technical team member involved in building and developing the company's initial machine learning systems and infrastructure. They typically have strong skills in programming, data modeling, and deploying ML models, often working closely with product teams during the startup or early-stage company formation. This role requires a combination of technical expertise and entrepreneurial mindset to shape the company's AI capabilities from the ground up.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the increasing adoption of AI and data-driven solutions across industries. They are sought after for their skills in algorithms, programming, and tools like Python and TensorFlow, with job growth expected to continue as AI applications expand.

Which 5 jobs will survive AI?

Founding Machine Learning Engineers are likely to continue playing a crucial role as AI advances, focusing on developing and deploying complex models that require specialized skills in programming, data science, and system architecture. Jobs that involve high levels of creativity, strategic decision-making, and human interaction—such as healthcare professionals, educators, skilled trades, and roles in management—are also expected to persist despite AI automation. These positions typically require emotional intelligence, critical thinking, and adaptability that AI cannot easily replicate.

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 Houston, TX are hiring for Founding Machine Learning Engineer jobs? Cities near Houston, TX with the most Founding Machine Learning Engineer job openings:
Infographic showing various Founding Machine Learning Engineer job openings in Houston, TX as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $122,971 per year, or $59.1 per hour.

Principal AI & Machine Learning Engineer, Spring, Texas, Onsite

Hewlett Packard Enterprise Development LP

Spring, TX • On-site

Full-time

Posted 28 days ago


Job description

Principal AI & Machine Learning Engineer, Spring, Texas, Onsite
This role has been designed as ''Onsite' with an expectation that you will primarily work from an HPE office.
Who We Are:
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world. Our culture thrives on finding new and better ways to accelerate what's next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
We are looking for an experienced Principal AI Engineer to drive the design, development, and deployment of AI/ML-powered applications. Candidate should have strong hands-on experience in application development, lead and mentor a team of AI developers, define best practices, and deliver scalable, production grade AI solutions aligned with business goals.
Location: Spring, Texas
Onsite daily work required
Key Responsibilities
  • Design, develop, and deploy AI applications, microservices, and APIs on Kubernetes-based infrastructure, ensuring scalability, reliability, and performance across development, staging, and production environments.
  • Build and maintain end-to-end AI pipelines covering deployment, monitoring, versioning, and continuous improvement using modern MLOps/AIOps tools and practices.
  • Lead and mentor a team of AI/ML engineers, conduct code reviews, and define best practices.
  • Continuously evaluate and adopt emerging AI tools, frameworks, LLM technologies, and open-source solutions to enhance platform capabilities and team productivity.
  • Collaborate closely with Business Analysts, Architect and technical teams to align AI engineering efforts with business objectives and ensure secure, compliant solutions.
  • Establish and maintain technical documentation, deployment runbooks and SOPs

Required Qualifications
  • 10+ years of hands-on experience in software engineering, with a strong focus on AI/ML application development and deployment.
  • Expertise in Kubernetes - container orchestration, Helm charts, pod management, scaling, and troubleshooting.
  • Strong experience with MLOps/AIOps tools and practices (e.g., MLflow, Kubeflow, Airflow, model registries, monitoring frameworks).
  • Hands-on experience with cloud platforms - Azure, AWS, or GCP, including their AI services.
  • Strong programming skills in Python; familiarity with FastAPI, Flask, or similar frameworks is mandatory.
  • Hands-on experience with CI/CD pipelines and tools such as GitOps, Docker, Jenkins, or GitHub Actions.
  • Lead and mentor development teams, drive delivery, and manage technical priorities.
  • Experience working with Agentic and GenAI frameworks and vector databases etc.
  • Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry) for AI workloads.
  • Good understanding of AI security, responsible AI principles, and governance frameworks.

Education
  • Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or a related field.

#unitedstates
What We Can Offer You:
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
#unitedstates
#operations
Job:
Engineering
Job Level:
TCP_05
"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
- United States of America: Annual Salary USD 152,000 - 349,000 in Texas
The listed salary range reflects base salary. Variable incentives may also be offered.""The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.
Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
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