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Entry Level Machine Learning Engineer Jobs in Baytown, TX

Scan Ninja Inc.

AI/ML Engineer - Cybersecurity

Houston, TX · On-site

$100 - $130/hr

Work closely with security engineers to validate model outputs in real-world scenarios * Define and ... Experience building and shipping machine learning or AI systems * Strong knowledge of NLP, LLMs ...

New

Urnet Inc

Engineer

Houston, TX · On-site

$100K - $150K/yr

As an Engineer in the Information industry, you will play a pivotal role in designing and ... Experience with machine learning frameworks such as TensorFlow or PyTorch. * Familiarity with ...

DPR Construction

MLOps Engineer

Houston, TX

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Oxy

AI Optimization Engineer

Houston, TX · On-site

... machine learning, and algorithmic techniques to build, maintain, and improve on decision systems ... Required : • Master's degree in Engineering, Applied Mathematics, or a related field. • Strong ...

EOG Resources, Inc.

Data Engineer II

Houston, TX

$109K - $131K/yr

Create and deploy both math and machine learning models to support current and future applications ... Bachelor's degree in Computer Science or Engineering or Information Technology.  MINIMUM ...

Capgemini

Entry Level Technologist

Houston, TX · On-site

As an Entry-Level Technology Consultant at Sogeti, you will join one of our core practices based on ... Explore emerging tech-from artificial intelligence/machine learning to cloud-native engineering ...

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

Entry Level Machine Learning Engineer information

See Baytown, TX salary details

$27.3K

$63.2K

$107.4K

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

As of Aug 7, 2026, the average yearly pay for entry level machine learning engineer in Baytown, TX is $63,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,900.00 and $71,500.00 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 are the most commonly searched types of Machine Learning Engineer jobs in Baytown, TX? The most popular types of Machine Learning Engineer jobs in Baytown, TX are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Baytown, TX? For Entry Level Machine Learning Engineer jobs in Baytown, TX, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Baytown, TX look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Baytown, TX are:
What cities near Baytown, TX are hiring for Entry Level Machine Learning Engineer jobs? Cities near Baytown, 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 Baytown, TX as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $63,156 per year, or $30.4 per hour.

Algorithm Engineer, Deep Learning & Vision (New Grad)

Bot Auto

Houston, TX • On-site

Full-time

Posted 10 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
Key Responsibilities
  • Model Implementation & Iteration: Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including perception, online mapping, and end-to-end planning.
  • Full Lifecycle Execution: Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification.
  • Cross-Functional Collaboration: Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks.
  • Literature Tracking: Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases.
How You'll Grow
This matters as much to us as what you'll ship.
  • You get a real mentor. Every engineer is paired with senior-level engineers developing you. Mentorship here is weighted toward design and judgment: how to frame a problem, what to build and why, how to tell whether a solution is actually right.
  • We promote fast. Managers are expected to push engineers to attempt work above their current level, and to promote in the next cycle when they deliver it.
Qualifications
Required:
  • Education: A Bachelor's, Master's, or Ph.D. (including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
  • You have trained neural networks. Coursework, research, personal projects, open-source work, and internships all count. We care that you have actually run the loop: built a model, trained it, found out why it was not working, and fixed it.
  • Core Knowledge: Strong theoretical foundation in machine learning and deep learning, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).
  • Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices).
  • Attributes: High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset.
Preferred:
  • Computer vision. Research or projects in computer vision, and particularly in 3D.
  • Specific Research Directions: Academic thesis or deeply focused research experience in one or more of the following domains:
    • Computer Vision (2D or 3D)
    • Online Mapping, Vectorization, or Visual SLAM
    • Prediction and Behavioral Modeling
  • Academic Achievements: A track record of research publications in machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS).
  • Engineering Plus: Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++).
  • Industry Exposure: Prior internship experience within the autonomous driving industry or advanced robotics labs.

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