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Junior Machine Learning Engineer Jobs in Terrell, TX

Varsity Tutors

Machine Learning Tutor

Dallas, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Plano, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Terrell, TX

Junior Machine Learning Engineer information

See Terrell, TX salary details

$29.5K

$63.2K

$96.5K

How much do junior machine learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for junior machine learning engineer in Terrell, TX is $63,248.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,700.00 and $70,500.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
More about Junior Machine Learning Engineer jobs

What cities near Terrell, TX are hiring for Junior Machine Learning Engineer jobs?

Cities near Terrell, TX with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you

Machine Learning Engineer, GenAI/ML - Vice President

J.P. Morgan

Plano, TX • On-site

Full-time

Medical, Retirement

Posted 19 days ago

Job description

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

JOB DESCRIPTION

Join a dynamic and diverse team that engineers large-scale, complex, and resilient technology solutions that drive our global business.

As a Machine Learning Engineer, GenAI/ML - Vice President 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.
  • 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 7+ 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.
  • 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.
  • 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.

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