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Quant Developer Internship Jobs in Texas (NOW HIRING)

... on quantitative feedback; knows and explains the "why" behind actions * Prioritized reaction ... Previous internship or co-op experience in a manufacturing environment or lab environment. * Strong ...

... data engineers and software engineers * Lead data science initiatives that impact operations ... Manage and mentor interns, junior data scientists and analysts * Translate advanced analytics ...

... on quantitative feedback; knows and explains the "why" behind actions * Prioritized reaction ... Previous internship or co-op experience in a manufacturing environment or lab environment. * Strong ...

... data engineers and software engineers * Lead data science initiatives that impact operations ... Manage and mentor interns, junior data scientists and analysts * Translate advanced analytics ...

Follow and help establish engineering standards (version control, documentation, testing, and data ... quantitative field (or equivalent demonstrated capability) * Demonstrated ability to build in ...

... Engineering, Physics, Quantitative Economics, or a related analytical discipline * 1-3 years of experience in data analysis, business analytics, or a similar quantitative role (internships and ...

... Engineering, Physics, Quantitative Economics, or a related analytical discipline * 1-3 years of experience in data analysis, business analytics, or a similar quantitative role (internships and ...

Previous internship or co-op experience in a manufacturing environment or lab environment. * Strong ... on quantitative feedback; knows and explains the "why" behind actions * Prioritized reaction ...

... engineering). * At least 2 years of insights CMI experience within beauty companies (including internships or apprenticeship * Understanding basic qualitative and quantitative CMi studies ...

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Quant Developer Internship information

What is a Quant Developer Internship?

A Quant Developer Internship is a temporary position, usually for students or recent graduates, that offers hands-on experience in quantitative finance and software development. Interns work with quantitative analysts and developers to design, implement, and optimize financial models and trading algorithms. The role typically involves programming, data analysis, and collaborating with other teams to solve real-world financial problems. This internship is an excellent opportunity for those interested in combining finance, mathematics, and computer science in a professional setting.

What is the difference between Quant Developer Internship vs Quant Analyst Internship?

AspectQuant Developer InternshipQuant Analyst Internship
Required CredentialsTypically pursuing or holding a degree in Computer Science, Mathematics, or related fieldsUsually pursuing or holding a degree in Finance, Economics, or related fields
Work EnvironmentHands-on coding, software development, and algorithm implementationData analysis, financial modeling, and strategy development
Employer & Industry UsageUsed in hedge funds, investment banks, and trading firms focusing on technology-driven rolesCommon in asset management firms, hedge funds, and financial institutions focusing on market analysis

While both internships involve finance and quantitative skills, Quant Developer Internships focus more on programming and software development, whereas Quant Analyst Internships emphasize financial analysis and modeling. Candidates should choose based on their strengths in coding versus financial analysis.

What are some common challenges faced during a Quant Developer Internship, and how can interns overcome them?

Quant Developer Interns often encounter challenges such as adapting to complex financial models, working with large datasets, and mastering specialized programming languages like Python or C++. To overcome these, interns should proactively seek guidance from senior team members, participate in regular code reviews, and allocate time to strengthen their understanding of both financial concepts and software development best practices. Collaboration and open communication within the team are crucial for navigating technical obstacles and successfully delivering project tasks.

What are the key skills and qualifications needed to thrive as a Quant Developer Intern, and why are they important?

To thrive as a Quant Developer Intern, you need a strong background in mathematics, statistics, and programming, typically demonstrated through a degree in quantitative fields like computer science, mathematics, or engineering. Familiarity with programming languages such as Python, C++, or Java, and experience using financial modeling tools or libraries are highly valued. Analytical thinking, attention to detail, and effective communication are critical soft skills for collaborating with teams and interpreting complex data. These skills and qualities are essential for developing robust quantitative models and contributing effectively to quantitative research and trading strategies.
What are the most commonly searched types of Quant Developer jobs in Texas? The most popular types of Quant Developer jobs in Texas are:
What cities in Texas are hiring for Quant Developer Internship jobs? Cities in Texas with the most Quant Developer Internship job openings:
Infographic showing various Quant Developer Internship job openings in Texas as of July 2026, with employment types broken down into 85% Full Time, 4% Part Time, 1% Temporary, 9% Contract, and 1% Nights. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Machine Learning/Deep Learning Engineer(PhD, New Grad)

Bot Auto

Houston, TX โ€ข On-site

Full-time

Posted 14 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 object detection, tracking, 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.
Qualifications
Required:
  • Education: An advanced degree (Master's or Ph.D., including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.
  • Core Knowledge: Strong theoretical foundation in machine learning, deep learning, and computer vision, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).
  • Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow, 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 (Targeted Research & Background):
  • Specific Research Directions: Academic thesis or deeply focused research experience in one or more of the following domains:
    • 3D Computer Vision / Bird's-Eye-View (BEV) Perception
    • Online Mapping, Vectorization, or Visual SLAM
    • Prediction and Behavioral Modeling
  • Academic Achievements: A proven track record of research publications in top-tier machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS) as a primary contributor.
  • 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 is highly desirable.