ZipRecruiter

Log In

1

Machine Learning Jobs in Plano, TX (NOW HIRING)

Photon

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

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 ...

Capital One

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Tihinsurance

Machine Learning Engineer

Dallas, TX

English (Required) Work Shift: 1st Shift (United States of America) Please review the following We are building the foundation of the machine learning function at a market-leading insurance company.

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners ...

previous page

Showing results 41-60

All JobsMachine Learning JobsMachine Learning Jobs in Plano, TX

Machine Learning information

See Plano, TX salary details

$24.4K

$40.8K

$84.2K

How much do machine learning jobs pay per year?

As of Aug 9, 2026, the average yearly pay for machine learning in Plano, TX is $40,756.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,100.00 and $44,000.00 per year, depending on experience, location, and employer.

What is a machine learning?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are the typical day-to-day responsibilities in a machine learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in a machine learning position?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

What are the most commonly searched types of Machine Learning jobs in Plano, TX? The most popular types of Machine Learning jobs in Plano, TX are:
What are popular job titles related to Machine Learning jobs in Plano, TX? For Machine Learning jobs in Plano, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning jobs in Plano, TX look for? The top searched job categories for Machine Learning jobs in Plano, TX are:
What cities near Plano, TX are hiring for Machine Learning jobs? Cities near Plano, TX with the most Machine Learning job openings:
Machine Learning jobs near you
Infographic showing various Machine Learning job openings in Plano, TX as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $40,756 per year, or $19.6 per hour.

Machine Learning Engineer - NJ

Photon

Addison, TX

$54 - $71.50/hr

Full-time

Re-posted yesterday

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.

Apply