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Senior Algorithm Engineer Jobs in Texas (NOW HIRING)

Raytheon

Senior Algorithm Systems Engineer

Plano, TX · On-site

$100K - $137K/yr

They are seeking a Senior Algorithm Systems Engineer to provide technical expertise and leadership across advanced aerospace sensor programs, focusing on algorithm development and performance ...

Retym

DSP Algorithm Engineer

Austin, TX · On-site

$141K - $165K/yr

Description For an exciting well-funded start-up, we are looking for a DSP Optical Communication Algorithm senior engineer. As an Algorithm Engineer you will be part of the R&D group developing next ...

Raytheon

Senior Algorithm Systems Engineer

Plano, TX

$100K - $136K/yr

Raytheon is seeking a seeking a Senior Algorithm Systems Engineer to support advanced aerospace sensor programs. You will provide technical expertise and leadership across multiple programs and ...

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Senior Algorithm Engineer information

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$55.4K

$117.9K

$171K

How much do senior algorithm engineer jobs pay per year?

As of Jul 30, 2026, the average yearly pay for senior algorithm engineer in Texas is $117,907.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $133,700.00 per year, depending on experience, location, and employer.

What is the difference between Senior Algorithm Engineer vs Data Scientist?

AspectSenior Algorithm EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, EE, or related; strong math and programming skillsBachelor's or Master's in CS, Statistics, or related; strong analytical and programming skills
Work EnvironmentDevelops algorithms for software, hardware, or embedded systems in tech companiesAnalyzes data to extract insights, often in tech, finance, or healthcare sectors
Industry UsageCommon in AI, robotics, and software developmentPrevalent in analytics, machine learning, and business intelligence

While both roles require strong programming and analytical skills, Senior Algorithm Engineers focus on designing and optimizing algorithms for technical systems, whereas Data Scientists analyze data to inform business decisions. The roles often overlap in AI and machine learning projects but serve different primary functions within organizations.

What are some common challenges faced by Senior Algorithm Engineers when deploying algorithms into production environments?

Senior Algorithm Engineers often encounter challenges such as ensuring that algorithms are both scalable and efficient when integrated into real-time systems. Balancing model accuracy with computational resource constraints is a frequent task, as well as addressing data inconsistencies and managing version control for iterative algorithm updates. Collaboration with software engineers and data engineers is essential to ensure smooth deployment, monitor performance, and quickly resolve any production issues. Staying updated with the latest frameworks and best practices also helps in overcoming these challenges.

What are the key skills and qualifications needed to thrive as a Senior Algorithm Engineer, and why are they important?

To thrive as a Senior Algorithm Engineer, you need advanced proficiency in mathematics, computer science, and algorithm design, usually supported by a relevant degree and extensive experience in the field. Expertise with programming languages such as Python or C++, proficiency with machine learning libraries, and familiarity with version control systems like Git are commonly required. Strong problem-solving skills, attention to detail, and the ability to communicate complex ideas clearly help set top candidates apart. These skills are crucial for developing robust, efficient solutions and collaborating effectively on challenging technical projects.

What does a Senior Algorithm Engineer do?

A Senior Algorithm Engineer is responsible for designing, developing, and optimizing complex algorithms that solve technical problems or enhance product performance. They often work with large datasets, machine learning models, or mathematical techniques to create efficient solutions. In addition to coding, they may collaborate with cross-functional teams, review the work of junior engineers, and help set the technical direction for algorithm development projects. Their expertise ensures that products and systems run efficiently and accurately.
What are the most commonly searched types of Algorithm Engineer jobs in Texas? The most popular types of Algorithm Engineer jobs in Texas are:
What cities in Texas are hiring for Senior Algorithm Engineer jobs? Cities in Texas with the most Senior Algorithm Engineer job openings:
Senior Algorithm Engineer jobs near you

Senior Algorithm Engineer, Reinforcement Learning

Bot Auto

Houston, TX • On-site

$99K - $137K/yr

Full-time

Medical, PTO

Re-posted 3 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 Senior 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.
Why Bot Auto?
We are a small, hyper-focused team on a mission to beat human cost-per-mile through technology. We recently successfully completed the industry's first fully humanless commercial truckload, proving that our vision is a reality. If you are passionate about AI, safety, and transforming logistics, we want to hear from you.

Apply