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Machine Learning Algorithms Jobs in Texas (NOW HIRING)

AtOrchard LLC

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard ... Design, develop, test, and refine algorithms and software that identify specific characteristics ...

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Machine Learning Algorithms information

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$23.8K

$39.7K

$82K

How much do machine learning algorithms jobs pay per year?

As of Sep 8, 2026, the average yearly pay for machine learning algorithms in Texas is $39,673.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What are machine learning algorithms?

Machine learning algorithms are computational methods that enable computers to learn patterns and make decisions or predictions from data without being explicitly programmed for each task. These algorithms can be classified into categories such as supervised learning, unsupervised learning, and reinforcement learning, each suited for different data and goals. Examples include decision trees, support vector machines, neural networks, and clustering algorithms. The choice of algorithm depends on the type of problem, the nature of the data, and the desired outcome.

What are the key skills and qualifications needed to thrive as a machine learning algorithms engineer?

To excel as a Machine Learning Algorithms Engineer, you need a solid background in mathematics, statistics, programming (especially Python or R), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow, PyTorch, or scikit-learn), data preprocessing tools, and cloud platforms is typically required, along with knowledge of version control systems. Strong analytical thinking, problem-solving abilities, and effective communication skills set top performers apart in this role. These skills and qualities are critical for designing robust models, collaborating with cross-functional teams, and translating complex data into actionable solutions.

What are some common challenges faced when collaborating with cross-functional teams as a machine learning algorithms specialist?

As a Machine Learning Algorithms specialist, collaborating with cross-functional teams such as data engineers, software developers, and product managers can present challenges like aligning on project goals, communicating complex technical concepts to non-experts, and integrating models into existing systems. It's important to establish clear communication channels, define shared objectives early, and actively participate in iterative feedback cycles. These practices help ensure that machine learning solutions are both technically sound and aligned with business needs.

What is the difference between Machine Learning Algorithms vs Data Scientists?

AspectMachine Learning AlgorithmsData Scientists
CredentialsKnowledge of algorithms, programming, statisticsAdvanced degrees in data science, statistics, or related fields
Work EnvironmentDeveloping, testing, and tuning algorithmsAnalyzing data, building models, interpreting results
Industry UsageEmbedded within data science workflows and toolsLeading data analysis projects, decision-making

While machine learning algorithms are the core tools used by data scientists, the role of a data scientist encompasses understanding, applying, and interpreting these algorithms within broader data analysis and business contexts. Machine learning algorithms are technical components, whereas data scientists integrate these tools to derive insights and inform strategies.

What careers are there in machine learning algorithms?

Careers in machine learning algorithms include roles such as machine learning engineer, data scientist, research scientist, and AI developer. These positions typically require skills in programming, statistics, and familiarity with tools like Python, TensorFlow, or PyTorch, and often involve developing models, analyzing data, and deploying AI solutions.

What are popular job titles related to Machine Learning Algorithms jobs in Texas?

For Machine Learning Algorithms jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Machine Learning Algorithms jobs in Texas look for?

The top searched job categories for Machine Learning Algorithms jobs in Texas are:

Machine Learning Algorithms jobs near you
Infographic showing various Machine Learning Algorithms job openings in Texas as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Machine Learning Engineer

Austin, TX • On-site

AtOrchard LLC
See more jobs at AtOrchard LLCexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

Description:Machine Learning EngineerRemote with occasional travel to Silver Spring, MD

About @Orchard:

@Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical science, data, technology, program management, and workforce solutions. Since 2010, we have built high-performing teams and disciplined delivery systems that help federal agencies launch complex programs, sustain performance, and achieve meaningful mission outcomes.


Position Summary:

@Orchard LLC is seeking an Machine Learning Engineer to support the National Oceanic and Atmospheric Administration (NOAA), Office of Ocean Exploration.


The Machine Learning Engineer will develop and apply machine learning capabilities to help NOAA Ocean Exploration analyze the large volumes of scientific data and video generated during ocean exploration expeditions. Working at the intersection of computer science, marine science, and data analytics, this position will develop software, algorithms, and analytical workflows that help identify scientifically significant characteristics, fauna, shapes, movement, and other features within complex scientific datasets and video streams.


The successful candidate will collaborate with marine scientists, engineers, data specialists, and other technical professionals to improve the efficiency and consistency of scientific data analysis. The role will help reduce manual review time, support annotation and characterization of observations, and create repeatable tools that enable scientists to extract meaningful information from increasingly large ocean exploration datasets.


This position is contingent upon contract award.


Mission Impact:

This position applies emerging AI and machine learning technologies to one of the world's most challenging data environments-ocean exploration. Your work will help NOAA scientists analyze massive volumes of expedition data and video more efficiently, accelerating the identification and characterization of marine life and other scientifically significant observations.


Key Responsibilities:


AI & Machine Learning Development

  • Develop machine learning capabilities for evaluating large volumes of ocean exploration data and streaming video.
  • Design, develop, test, and refine algorithms and software that identify specific characteristics, shapes, movement, fauna, and other features within scientific data and video. 
  • Develop computer-language subroutines, scripts, and programs that support automated or semi-automated data analysis, annotation, and characterization. 
  • Apply appropriate machine learning and computer vision techniques to improve the efficiency and consistency of scientific data review. 
  • Evaluate model performance and refine approaches based on scientific objectives and observed results. 


Scientific Data & Video Analysis

  • Work with large scientific datasets and high-volume expedition video to identify patterns and features relevant to ocean exploration. 
  • Collaborate with marine scientists to translate scientific questions and observation requirements into computational approaches.
  • Support development of tools that enable scientists to efficiently locate, annotate, classify, and characterize observations.
  • Assist in developing repeatable analytical workflows that can be applied to future expeditions and datasets. 
  • Support integration of AI/ML outputs into broader scientific data analysis, annotation, and ocean exploration workflows.


Software Development & Documentation

  • Develop maintainable and reusable code supporting machine learning and data-analysis capabilities.
  • Document software development, algorithms, workflows, model changes, and system updates to support future corrections and enhancements. 
  • Test and troubleshoot applications and analytical workflows to ensure reliable performance. 
  • Recommend improvements to software, analytical methods, and machine learning workflows. 
  • Support software corrections and updates as required. 


Scientific Collaboration

  • Collaborate with marine scientists, GIS specialists, web developers, engineers, and other technical professionals. 
  • Participate in technical discussions, scientific meetings, and project planning activities. 
  • Translate technical machine learning concepts into understandable information for scientific and program stakeholders. 
  • Support technical reports, presentations, demonstrations, and other program deliverables. 


Operational Support

  • Support response to urgent software or analytical issues affecting supported capabilities, including occasional work outside normal business hours when required
  • Support troubleshooting and resolution of issues affecting machine learning applications and associated web or data capabilities.
Requirements:
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Marine Science, Oceanography, or related discipline. Master's degree preferred.
  • Experience developing or applying machine learning solutions for data analysis, computer vision, video analysis, or related applications.
  • Programming experience in Python or another modern programming language.
  • Experience working with large datasets and developing repeatable data-analysis workflows.
  • Understanding of machine learning concepts, model development, evaluation, and optimization.
  • Strong analytical and problem-solving skills.
  • Ability to collaborate effectively with scientists and technical professionals from different disciplines.
  • Excellent written and verbal communication skills.
  • Proficiency with Microsoft Office 365, Google Workspace, and Adobe Acrobat.
  • Occasional domestic travel may be required to support scientific meetings, workshops, planning sessions, training activities, or other program requirements consistent with contract needs.
  •  Must be eligible to obtain and maintain a Department of Commerce / NOAA federal background investigation and suitability determination and be authorized to work in the United States without employer sponsorship. 

Preferred Skills and Experience:

  • Experience applying AI or machine learning to scientific, environmental, marine, or oceanographic datasets is preferred.
  • Experience with computer vision, image recognition, object detection, video analytics, or image classification.
  • Experience working with high-volume video or streaming data.
  • Experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with scientific Python libraries and data-analysis tools.
  • Experience supporting NOAA, other federal agencies, academic research organizations, or marine science programs.
  • Familiarity with marine organisms, oceanographic data, or scientific expedition environments.


Technical Skills:

  • Python 
  • Data Analysis 
  • Large-Scale Data Processing 
  • Algorithm Development 
  • Software Testing & Troubleshooting 
  • Scientific Data Workflows 


Compensation: The anticipated salary range for this position depends on the candidate's qualifications, relevant scientific experience, education, and overall experience supporting similar federal programs.


What We Offer:

Competitive base salary with opportunities for advancement, career growth and professional development, work-life balance, comprehensive benefits including health, dental, vision, life insurance, 401(k), generous PTO, and paid federal holidays.


If you are passionate about artificial intelligence, machine learning, and applying innovative technology to ocean exploration, we encourage you to join our team and help transform massive volumes of scientific data into discoveries that advance our understanding of the world's oceans.


@Orchard is an equal opportunity employer. We encourage all qualified candidates to apply, regardless of race, gender, age, disability, or other protected characteristics.


To learn more about our other exciting opportunities, visit our Jobs Page at www.atorchard.com.