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Machine Learning Algorithms Jobs in Texas (NOW HIRING)

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Understanding of widely used machine learning algorithms, model-training methods, evaluation techniques, and hyperparameter tuning. * Ability to translate complex technical topics for both technical ...

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Understanding of widely used machine learning algorithms, model-training methods, evaluation techniques, and hyperparameter tuning. * Ability to translate complex technical topics for both technical ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$184K - $324K/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 ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$184K - $324K/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 ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$184K - $324K/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 ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

Degree in Computer Science, Machine Learning, or Related disciplines; and 2+ years of relevant experience • Excellence in Python • Deep expertise in algorithms and data structures • Exposure to ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

Research and implement ML algorithms for a variety of business problems * Automate processes for ... Machine learning (ML) algorithms * Predictive modeling and analysis * Data visualization software ...

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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 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 Developer

Dallas, TX • On-site

Addison Group
See more jobs at Addison Groupexternal

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 12 days ago

Job description

Job Title: Machine Learning Developer
Location (city, state): Dallas, Texas - onstie 5x a week
Assignment Type: Direct Hire
Pay: $115,000-$140,000 annually, plus a short-term incentive and long-term incentive.
Benefits: This position is eligible for medical, dental, vision, and 401(k). The company offers fully paid family benefits, a generous 401(k) match, and a competitive paid-time-off program.
Our client is a well-established energy organization with significant operations in the Permian Basin. The company is expanding its artificial intelligence and machine learning capabilities and offers a collaborative environment where employees are trusted to take ownership, contribute ideas, and influence technical direction.
We are seeking a Machine Learning Developer to serve as the first dedicated ML engineering professional within a newly established AI/ML function. This individual will create the MLOps framework, development standards, and platform foundation needed to move machine learning models from experimentation into secure, reliable production environments.
This is a hands-on individual contributor role with significant influence over the organization's future machine learning strategy. The successful candidate will be comfortable setting technical direction, recommending new approaches, and performing the detailed engineering work required to implement those recommendations. This opportunity is ideal for someone who enjoys building programs from the ground up and working in a fast-moving, entrepreneurial environment.
Key Responsibilities:
  • Develop the organization's MLOps strategy, technical standards, reusable workflows, and preferred process for moving models into production.
  • Build and support machine learning solutions within the Databricks environment.
  • Collaborate with data scientists to deploy models using tools such as MLflow, AutoML, Unity Catalog, and Databricks Model Serving.
  • Create automated CI/CD processes for model training, deployment, testing, and promotion between environments.
  • Manage the full model lifecycle, including experiment tracking, model registration, version control, lineage, governance, and user access.
  • Implement monitoring and validation processes for production models, features, and source data.
  • Establish operational visibility for ML systems and assist with troubleshooting and production support when issues arise.
  • Develop standards for data quality, feature reliability, schema validation, and data version management.
  • Produce technical documentation, reference designs, reusable templates, and engineering playbooks.
  • Lead code reviews and share best practices with data science and engineering professionals.
  • Work with business leaders, data scientists, data engineers, and IT teams to define requirements and encourage adoption of shared ML frameworks.
  • Research emerging technologies and recommend enhancements to machine learning delivery, including GenAI, agent-based systems, and AI-assisted development tools.
  • Present technical recommendations to stakeholders and confidently explain or defend a position when viewpoints differ.

Qualifications:
  • Bachelor's degree in computer science, data science, engineering, mathematics, statistics, or a related discipline is required.
  • Three to five years of experience developing, deploying, or supporting machine learning or data-intensive production systems is preferred; candidates with more advanced experience are also encouraged to apply.
  • Hands-on experience with Databricks MLflow and AutoML is required.
  • Advanced Python skills with the ability to create clean, tested, and maintainable production code.
  • Strong SQL capabilities and familiarity with Spark or another distributed data-processing technology.
  • Experience implementing or supporting MLOps practices such as automated pipelines, model deployment, production monitoring, and lifecycle governance.
  • Knowledge of software development fundamentals, including Git, unit testing, CI/CD, and common application design principles.
  • Understanding of widely used machine learning algorithms, model-training methods, evaluation techniques, and hyperparameter tuning.
  • Ability to translate complex technical topics for both technical and nontechnical audiences.
  • Strong analytical, organizational, interpersonal, and problem-solving skills.
  • Ability to work independently, manage competing priorities, and operate with limited supervision.

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