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Machine Learning Engineer Jobs in College Station, TX

Texas A&M University

Instrument Maker III

College Station, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... the programming and operation of multiple types of computerized machines and related equipment ... Texas A&M University is committed to enriching the learning and working environment by promoting a ...

Tamus

Instrument Maker III

College Station, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... the programming and operation of multiple types of computerized machines and related equipment ... Texas A&M University is committed to enriching the learning and working environment by promoting a ...

City of Bryan, TX

City Engineer

Bryan, TX · On-site

$140K - $170K/yr

Position Details Position Information Posting Number 2026530 Position Title City Engineer Position ... machines, and occasionally lifting and/or moving objects up to and including 25 pounds. Working ...

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Showing results 41-54

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in College Station, TX

Machine Learning Engineer information

See College Station, TX salary details

$26.1K

$106.5K

$160K

How much do machine learning engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for machine learning engineer in College Station, TX is $106,492.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,900.00 and $128,200.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What are the most commonly searched types of Machine Learning Engineer jobs in College Station, TX?

The most popular types of Machine Learning Engineer jobs in College Station, TX are:

What are popular job titles related to Machine Learning Engineer jobs in College Station, TX?

For Machine Learning Engineer jobs in College Station, TX, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in College Station, TX look for?

The top searched job categories for Machine Learning Engineer jobs in College Station, TX are:

What cities near College Station, TX are hiring for Machine Learning Engineer jobs?

Cities near College Station, TX with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in College Station, TX as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $106,492 per year, or $51.2 per hour.

Software Engineer, Data Infrastructure & Acquisition - College Station, TX, USA

Speechify

College Station, TX • On-site

$94K - $113K/yr

Full-time

Re-posted 11 days ago

Job description

The mission of Speechify is to make sure that reading is never a barrier to learning.
Over 50 million people use Speechify's text-to-speech products to turn whatever they're reading - PDFs, books, Google Docs, news articles, websites - into audio, so they can read faster, read more, and remember more. Speechify's text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.
Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting - Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.
Overview
We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.
What You'll Do
  • Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
  • Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
  • Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
  • Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team's dataset roadmap to power Speechify's next-generation consumer and enterprise products.

An Ideal Candidate Should Have
  • BS/MS/PhD in Computer Science or a related field.
  • 5+ years of industry experience in software development.
  • Proficiency with bash/Python scripting in Linux environments
  • Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
  • Experience with web crawlers, large-scale data processing workflows is a plus
  • Ability to handle multiple tasks and adapt to changing priorities.
  • Strong communication skills, both written and verbal.

What we offer
  • A fast-growing environment where you can help shape the company and product.
  • An entrepreneurial-minded team that supports risk, intuition, and hustle.
  • A hands-off management approach so you can focus and do your best work.
  • An opportunity to make a big impact in a transformative industry.
  • Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
  • Opportunity to work on a life-changing product that millions of people use.
  • Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
  • Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience
Think you're a good fit for this job?
Tell us more about yourself and why you're interested in the role when you apply.
And don't forget to include links to your portfolio and LinkedIn.
Not looking but know someone who would make a great fit?
Refer them!
Speechify is committed to a diverse and inclusive workplace.
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Apply