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Neural Engineer Jobs in Houston, TX (NOW HIRING)

Bah

University - Human Spaceflight Engineer

Houston, TX · On-site

$52K - $108K/yr

Experience developing Graph Neural Networks and Model Predictive Control frameworks * Experience ... Experience programming in Python, NVIDIA Warp, or C++ Compensation At Booz Allen, we celebrate your ...

Bah

University, Human Spaceflight Engineer

Houston, TX · On-site

$52K - $108K/yr

Experience developing Graph Neural Networks and Model Predictive Control frameworks * Experience ... Experience programming in Python, NVIDIA Warp, or C++ Compensation At Booz Allen, we celebrate your ...

Accenture

Responsible AI Engineer

Houston, TX · On-site

DeepLearning, Neural Networks, Generative AI * Natural Language Processing, Text Mining, Computer ... Proficiency in programming languages like Python, R, or Java. * Familiarity with AI and machine ...

Pwc

AI & GenAI Data Scientist - Manager

Houston, TX

$99K - $232K/yr

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy ... Applying deep learning techniques and neural networks to improve predictive analytics ...

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Showing results 21-40

All JobsNeural Engineer JobsNeural Engineer Jobs in Houston, TX

Neural Engineer information

See Houston, TX salary details

$50K

$93.8K

$170.6K

How much do neural engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for neural engineer in Houston, TX is $93,790.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,600.00 and $111,300.00 per year, depending on experience, location, and employer.

What does a neural engineer do?

A Neural Engineer applies principles from neuroscience, engineering, and computer science to develop technologies that interface with the nervous system. This includes designing brain-computer interfaces, neuroprosthetics, and medical devices for treating neurological disorders. They work with signal processing, machine learning, and biomedical hardware to understand and manipulate neural activity. Their work has applications in healthcare, rehabilitation, and human augmentation.

What are the key skills and qualifications needed to thrive as a neural engineer?

To thrive as a Neural Engineer, you need a strong background in biomedical engineering, neuroscience, and signal processing, often supported by an advanced degree in a related field. Proficiency with tools like MATLAB, Python, neural data acquisition systems, and familiarity with medical device regulations or certifications are commonly required. Problem-solving abilities, interdisciplinary teamwork, and effective communication set standout candidates apart. These skills and qualities are crucial for innovating and safely developing neural devices and technologies that bridge engineering and neuroscience.

What types of projects and collaborations can a neural engineer expect to be involved in?

As a Neural Engineer, you may work on projects ranging from designing brain-computer interfaces and neural prosthetics to analyzing complex neural signals for clinical or research applications. Collaboration with neuroscientists, clinicians, software developers, and hardware engineers is common, ensuring a multidisciplinary approach to solving neurological challenges. Your daily responsibilities might include data analysis, prototyping, testing devices, and presenting findings to your team. This role offers opportunities to influence cutting-edge research and directly contribute to advancements in healthcare and neurotechnology.

How much does a neural engineer make?

The average salary for a neural engineer typically ranges from $80,000 to $130,000 annually, depending on experience, education, and location. Professionals in this field often hold advanced degrees in neuroscience, engineering, or related areas and work in research institutions, healthcare, or tech companies specializing in brain-computer interfaces and neural technologies.

Is neural engineering a good career?

Neural engineering is a growing field that combines neuroscience, engineering, and computer science to develop technologies like brain-computer interfaces and neural prosthetics. It offers opportunities in research, healthcare, and industry, often requiring advanced degrees and technical skills. The career can be rewarding for those interested in innovative medical solutions and interdisciplinary work.

What jobs can you do with neural engineering?

Neural engineers can work in research and development roles focused on brain-computer interfaces, neural prosthetics, and neurotechnology devices. They often find employment in healthcare, biotech, and academic settings, applying skills in signal processing, neuroscience, and engineering design to develop innovative solutions for neurological disorders and cognitive enhancement.

What are the most commonly searched types of Neural Engineer jobs in Houston, TX?

The most popular types of Neural Engineer jobs in Houston, TX are:

What are popular job titles related to Neural Engineer jobs in Houston, TX?

For Neural Engineer jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Neural Engineer jobs in Houston, TX look for?

The top searched job categories for Neural Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Neural Engineer jobs?

Cities near Houston, TX with the most Neural Engineer job openings:

Neural Engineer jobs near you
Infographic showing various Neural Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $93,790 per year, or $45.1 per hour.

Algorithm Engineer, Reinforcement Learning

Bot Auto

Houston, TX • On-site

$56 - $77/hr

Full-time

Medical, PTO

Re-posted 15 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 startup and the wisdom of seasoned experts, our team has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create groundbreaking solutions that propel the future of transportation. Join us and transform your ideas into reality.
Role Overview
We are seeking a ML/RL Engineer to join our Algo team and drive the development of our unified behavioral architecture. In this role, you will help bridge the gap between simulation and the real world by developing a scalable policy framework that represents both our L4 ego-policy and a diverse population of simulated agents. You will work at the intersection of Multi-Agent Reinforcement Learning (MARL) and safety-critical system design to ensure our autonomous semi-trucks navigate highways with superhuman safety and precision.
Key Responsibilities
  • Behavioral Modeling: Develop and train diverse, conditioned policies that simulate realistic driving behaviors to stress-test and validate our autonomous driving stack.
  • Safety-Constrained Learning: Lead the research and implementation of advanced RL algorithms to ensure safety metrics are treated as primary constraints in the learning process.
  • Reward & Objective Design: Collaborate with cross-functional teams to design robust reward functions and evaluation metrics that balance safety, progress, and comfort.
  • Scalable Training Pipelines: Contribute to the optimization of our large-scale, high-throughput training environments to enable rapid iteration on complex multi-agent scenarios.
  • Model Architecture: Advance our state-of-the-art neural architectures to improve spatial reasoning, long-horizon planning, and interaction modeling.
  • Cross-Team Collaboration: Work closely with Simulation and Planning teams to integrate research-grade models into production-quality, safety-critical software.
Required Qualifications
  • Professional RL Experience: Proven track record of training and deploying deep RL algorithms (e.g., PPO, SAC) for complex, real-world robotic or autonomous systems.
  • Technical Mastery: Expertise in Python and PyTorch; strong understanding of modern deep learning architectures and optimization techniques.
  • Academic Background: MS or PhD in Computer Science, Robotics, or a related quantitative field.
  • Scientific Intuition: Ability to diagnose and solve fundamental challenges in RL training, such as variance management and distribution shift.
Preferred Qualifications
  • Safe RL Specialization: Experience with constrained optimization or safety-critical learning frameworks.
  • Multi-Agent Systems: Background in MARL training stability, including self-play and decentralized execution strategies.
  • Autonomous Driving Domain: Familiarity with vehicle dynamics and behavior planning, particularly for long-haul highway environments.
Additional Information
  • Compensation: Competitive salary based on experience, with opportunities for performance bonuses and equity.
  • Benefits: Comprehensive health insurance, paid time off, and the opportunity to work at the forefront of the autonomous trucking industry.

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