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Startup Machine Learning Intern Jobs in Conroe, TX

Citadel

Software Engineer - Intern (US)

Houston, TX · On-site

$4.5K - $5.8K/wk

You'll have access to state-of-the-art tools and apply innovative techniques including distributed computing, natural language processing, machine learning and more. As an intern, you'll get to ...

Citadel

Software Engineer - Intern (US)

Houston, TX

$112.50 - $145/hr

You'll have access to state-of-the-art tools and apply innovative techniques including distributed computing, natural language processing, machine learning and more. As an intern, you'll get to ...

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All JobsStartup Machine Learning Intern JobsStartup Machine Learning Intern Jobs in Conroe, TX

Startup Machine Learning Intern information

See Conroe, TX salary details

$21.8K

$36.5K

$75.3K

How much do startup machine learning intern jobs pay per year?

As of Aug 8, 2026, the average yearly pay for startup machine learning intern in Conroe, TX is $36,457.00, according to ZipRecruiter salary data. Most workers in this role earn between $27,800.00 and $39,400.00 per year, depending on experience, location, and employer.

What are the typical responsibilities of a startup machine learning intern, and how do they contribute to the team's goals?

As a Startup Machine Learning Intern, you can expect to work on a mix of data preparation, model development, and experimental analysis. Interns often collaborate closely with data scientists, engineers, and product managers to prototype and test machine learning solutions that address real business problems. You'll likely take ownership of individual tasks, such as cleaning datasets, building and validating models, and reporting results to the team. This hands-on environment offers exposure to the full machine learning pipeline and provides opportunities to make meaningful contributions to the company's progress.

What does a startup machine learning intern do?

A Startup Machine Learning Intern typically assists in developing, testing, and deploying machine learning models to solve real-world business problems in a fast-paced startup environment. Their responsibilities may include data preprocessing, feature engineering, model selection, and performance evaluation. Interns often collaborate closely with data scientists and software engineers, gaining hands-on experience with tools like Python, TensorFlow, or PyTorch. The role provides an opportunity to contribute directly to innovative projects and learn about the startup culture.

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

To thrive as a Startup Machine Learning Intern, you typically need a solid understanding of machine learning concepts, programming proficiency in Python, and coursework or experience in data science or statistics. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving skills, initiative, and the ability to communicate complex ideas clearly are essential soft skills in a dynamic startup environment. These competencies enable interns to quickly contribute to projects, adapt to evolving tasks, and support innovation within fast-paced teams.

What is the difference between Startup Machine Learning Intern vs Startup Data Scientist?

AspectStartup Machine Learning InternStartup Data Scientist
Required CredentialsTypically pursuing or recent graduate in CS, Data Science, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields; often with experience
Work EnvironmentEntry-level, learning-focused, collaborative team settingAdvanced projects, strategic decision-making, leadership roles
Employer & Industry UsageStartups, tech companies, research labsStartups, tech firms, larger organizations with data teams

The Startup Machine Learning Intern role is an entry-level position aimed at gaining practical experience in machine learning within startup environments. In contrast, a Startup Data Scientist typically has more experience and handles complex data analysis, model development, and strategic insights. The internship is ideal for students or recent grads, while data scientists are more senior roles focused on driving data-driven decisions.

What are popular job titles related to Startup Machine Learning Intern jobs in Conroe, TX? For Startup Machine Learning Intern jobs in Conroe, TX, the most frequently searched job titles are:
What job categories do people searching Startup Machine Learning Intern jobs in Conroe, TX look for? The top searched job categories for Startup Machine Learning Intern jobs in Conroe, TX are:
What cities near Conroe, TX are hiring for Startup Machine Learning Intern jobs? Cities near Conroe, TX with the most Startup Machine Learning Intern job openings:
Startup Machine Learning Intern jobs near you

Algorithm Engineer, Deep Learning & Vision (New Grad)

Bot Auto

Houston, TX • On-site

Full-time

Posted 11 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.
QualificationsRequired:
  • 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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