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Machine Learning Engineer Jobs in Prosper, TX (NOW HIRING)

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Develop machine learning models and algorithms to address business needs. Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions. Clean ...

Senior ML Engineer

Addison, TX · On-site

$101K - $138K/yr

Responsibilities: • Develop machine learning models and algorithms to address business needs. • Collaborate with data scientists and software engineers to design and implement scalable and ...

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable ... Pipeline Engineering: Develop and optimize data processing pipelines for data preprocessing ...

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable ... Pipeline Engineering: Develop and optimize data processing pipelines for data preprocessing ...

Showing results 41-60

Machine Learning Engineer information

See Prosper, TX salary details

$28.8K

$117.9K

$177.2K

How much do machine learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for machine learning engineer in Prosper, TX is $117,925.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,000.00 and $141,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Prosper, TX? The most popular types of Machine Learning Engineer jobs in Prosper, TX are:
What are popular job titles related to Machine Learning Engineer jobs in Prosper, TX? For Machine Learning Engineer jobs in Prosper, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Prosper, TX look for? The top searched job categories for Machine Learning Engineer jobs in Prosper, TX are:
What cities near Prosper, TX are hiring for Machine Learning Engineer jobs? Cities near Prosper, TX with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Prosper, TX as of August 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 100% In-person job distribution, with an average salary of $117,925 per year, or $56.7 per hour.

Machine Learning Engineer, Senior Associate

J.P. Morgan

Plano, TX • On-site

$117K - $154K/yr

Full-time

Medical, Retirement

Posted 10 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Shape the future of technology and drive significant business impact in financial services. Join our team and help us develop game changing, high-quality solutions.

As a AI/ML Engineer Senior Associate within Banking & Wealth Management, Consumer & Community banking Home Lending Technology team, you will be tasked with the design, construction, and maintenance of our AIOps solution. This role demands a profound knowledge of AI/ML technologies, IT infrastructure, and platform engineering.

Job Responsibilities:

  • Lead the design, development, and deployment of generative AI solutions, ensuring alignment with business objectives and technical requirements. 
  • Demonstrate deep expertise in generative AI technologies, contributing to the development of POCs and evaluating new methodologies to enhance AI capabilities.
  • Exhibit strong proficiency in Java or Python, with the ability to architect and build complex AI models from scratch. Ensure the delivery of secure, high-quality production code and utilize experience with React or Angular to create intuitive user interfaces for AI applications. Conduct thorough code reviews to maintain high standards of code quality.
  • Leverage AWS experience to implement best practices in AI integration, ensuring quality, security, and efficiency across AI projects.
    Identify and implement opportunities to automate processes and enhance the operational stability of generative AI applications and systems.
  • Actively participate in communities of practice to promote the adoption and awareness of new generative AI technologies, fostering a culture of continuous innovation.

Required qualifications, capabilities, and skills:

  • Minimum 5+ years of strong proficiency in Python or Java, with the ability to architect and build complex AI models from scratch.
  • Two years of experience in generative AI development and prompt engineering.
  • Proven experience in system design, application development, testing, and operational stability in AI projects.
  • Minimum 5+ years of strong experience with React or Angular with minimum 2+ years of AWS experience.
  • Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, applied to AI projects.
  • Experience with LLM models and agentic tools.

Preferred qualifications, capabilities, and skills:

  • Experience with AI model optimization and performance tuning to ensure efficient and scalable AI solutions.
  • Familiarity with data engineering practices to support AI model training and deployment.
  • Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning with experience with AI/ML libraries and tools such as TensorFlow, PyTorch, Scikit-learn, and Keras.

ABOUT US

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.