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Entry Level Machine Learning Engineer Jobs in Georgetown, TX

Fluidstack

Machine Learning Engineer

Austin, TX · On-site

$224K - $279K/yr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX · On-site

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

Lauretta AI LLC

Machine Learning Engineer L-1

Austin, TX

$80K - $93K/yr

* Develop high-quality, maintainable code to build and deploy computer vision modules and machine learning models as part of an AI pipeline * Works with data and software engineering team to integrate ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Georgetown, TX

Entry Level Machine Learning Engineer information

See Georgetown, TX salary details

$27.9K

$64.4K

$109.6K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for entry level machine learning engineer in Georgetown, TX is $64,446.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,800.00 and $72,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What job categories do people searching Entry Level Machine Learning Engineer jobs in Georgetown, TX look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Georgetown, TX are:
What cities near Georgetown, TX are hiring for Entry Level Machine Learning Engineer jobs? Cities near Georgetown, TX with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Georgetown, TX as of August 2026, with employment types broken down into 33% Internship, and 67% Full Time. Highlights an 33% In-person, 34% Hybrid, and 33% Remote job distribution, with an average salary of $64,446 per year, or $31 per hour.

Machine Learning Engineer

Fluidstack

Austin, TX • On-site

$224K - $279K/yr

Full-time

Posted 22 days ago

Job description

About Fluidstack
We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.
We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.
We hire people who care deeply about this problem space. If that is you, please apply!
How We Operate
  • Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
  • Velocity. We drive everything forward as fast as possible.
  • First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.
  • Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.
Role Scope
  • Build ML and LLM systems that run inside the company's operations: forecasting build timelines, flagging schedule risk, and extracting structure from vendor documents.
  • Own models end to end, from problem framing and data through deployment, evaluation, and iteration in production.
  • Ship agentic systems with real guardrails, authorization, audit, and evals, so agents act on company systems instead of just advising.
  • Partner with data engineering and product pods to put predictions in the tools people already use.
What We're Looking For
  • The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.
  • You've shipped ML or LLM features to production and owned them after launch.
  • You've built evaluation harnesses that told you the truth about model quality before users did.
  • You reach for the simplest model that works and can defend the choice.
  • You've worked hands-on with LLM APIs, fine-tuning, or retrieval systems on real business problems.
  • You write production-quality code and work fluently with AI coding tools.
  • Bonus: Forecasting or scheduling problems. Document extraction at scale. Agentic frameworks and MCP. Temporal or workflow engines.

We are committed to pay equity and transparency.
Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.

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