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Machine Learning Algorithms Jobs in Texas (NOW HIRING)

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights. * Apply expertise in data mining and machine learning techniques, including ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights. * Apply expertise in data mining and machine learning techniques, including ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Required : • Strong understanding of fundamental machine learning algorithms and neural network techniques. • Expertise in at least one modern machine learning domain, such as computer vision ...

News Corporation

Senior Manager, Machine Learning

Austin, TX · On-site

$120 - $160/hr

  • Medical

  • Dental

  • Vision

  • Retirement

Direct development of predictive, explanatory models and machine learning algorithms. * Design and build machine learning solutions to drive revenue growth, customer retention and support strategic ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

  • Medical

Specific tools, technologies, certifications, or travel requirements may be customized by the hiring manager RESPONSIBILITIES Design and implement machine learning algorithms and models for various ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

  • Medical

Specific tools, technologies, certifications, or travel requirements may be customized by the hiring manager RESPONSIBILITIES • Design and implement machine learning algorithms and models for ...

Apple

Machine Learning Engineer, Apple Store Online

Austin, TX

$129K - $225K/yr

  • Medical

  • Dental

  • Retirement

... algorithms used to drive the Apple Online experience! This role spans central areas of our Apple ... Description To be successful, you need a strong machine learning background, proven software ...

Apple

Machine Learning Engineer, Apple Store Online

Austin, TX

$129K - $225K/yr

  • Medical

  • Dental

  • Retirement

... algorithms used to drive the Apple Online experience! This role spans central areas of our Apple ... Description To be successful, you need a strong machine learning background, proven software ...

Apple

Machine Learning Engineer, Apple Store Online

Austin, TX

$129K - $225K/yr

  • Medical

  • Dental

  • Retirement

... algorithms used to drive the Apple Online experience! This role spans central areas of our Apple ... Description To be successful, you need a strong machine learning background, proven software ...

Q2 India

Machine Learning Engineer

Austin, TX · On-site

$100 - $130/hr

  • Medical

RESPONSIBILITIES** • Design and implement machine learning algorithms and models for various business applications • Conduct research and experimentation to advance machine learning capabilities ...

Apple, Inc.

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

... algorithms used to drive the Apple Online experience! The role spans central areas of our Apple ... Description To be successful, candidates will need a machine learning background, proven software ...

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All JobsMachine Learning Algorithms JobsMachine Learning Algorithms Jobs in Texas

Machine Learning Algorithms information

See Texas salary details

$23.8K

$39.7K

$82K

How much do machine learning algorithms jobs pay per year?

As of Aug 19, 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 August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Machine Learning Engineer - NJ

Photon

Addison, TX • On-site

$54 - $71.50/hr

Full-time

Re-posted 11 days ago

Job description


Summary:
We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and engineering teams to solve complex business problems, identify data-driven opportunities, and create personalized experiences for customers. You will be responsible for building end-to-end machine learning solutions, implementing models in production, and working with various data frameworks and tools such as Python, Spark, and Databricks.
Key Responsibilities: Analytics Model Development:
  • Analyze use cases and design appropriate analytics models using statistical and machine learning algorithms tailored to specific business requirements.
  • Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights.
  • Apply expertise in data mining and machine learning techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.

Data Engineering and Preparation:
  • Extend and augment company data with third-party data to enrich analytics capabilities.
  • Enhance data collection procedures to include necessary information for building analytics systems.
  • Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing data formats using Python data frameworks (e.g., Pandas, NumPy).

Machine Learning Model Implementation:
  • Implement machine learning models, considering both performance and scalability using tools like PySpark in Databricks.
  • Design and build infrastructure to facilitate large-scale data analytics and experimentation.
  • Work with tools like Jupyter Notebooks for data exploration and model development.

What We're Looking For:
  • Educational Background: Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A PhD is preferred but not necessary.
  • Experience:
    • At least 5 years of experience in data analytics, with a strong understanding of core statistical algorithms such as classification and regression analysis.
    • High-level knowledge of analytics use cases such as language analysis, assortment optimization, promotional planning, dynamic pricing, markdown optimization, labor scheduling, and optimization.
  • Technical Skills:
    • Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
    • Proficiency in using analytics platforms like Databricks for large-scale data processing.
    • At least 4 years of continuous experience with Spark, particularly PySpark implementation.
    • Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.

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