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Java Machine Learning Jobs in Texas (NOW HIRING)

Meta

Software Engineer, Machine Learning

Austin, TX · On-site

$154K/yr

Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams ... Knowledge developing and debugging in C/C++ and Java * Demonstrated ability to integrate AI tools ...

SynergisticIT

Junior Java/DevOps Engineer

Dallas, TX

We want data science/machine learning/data analyst and Java full stack candidates. For data science/machine learning positions required skills include a bachelors degree or masters degree in computer ...

Sarian, Inc.

Java Full stack Developer

Plano, TX · On-site

$50.25 - $64.75/hr

Java , J2EE/ Spring MVC. * Secondary: UI - React JS, ECMA 6 etc. * Good to Have ... Machine Learning ( Llama, Python etc). * Experience: Minimum 7 years. * This is a Full stack ...

Striveworks

Staff Machine Learning Engineer

Austin, TX · On-site +1

The Role As a Staff Machine Learning Engineer at Striveworks, you will be challenged-and trusted-on ... Rust, C++, Java, Scala, etc.) * Proficiency in the design and delivery of algorithms, data ...

Dminds Solutions Inc.

Java AI/ML Developer

Plano, TX · Hybrid

$49 - $63.50/hr

Hiring: Java AI/ML Developer Type: Hybrid Location: Plano, TX We are looking for an experienced ... Strong understanding of machine learning algorithms, model evaluation, and data processing

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How much do java machine learning jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for java machine learning in Texas is $52.82, according to ZipRecruiter salary data. Most workers in this role earn between $45.67 and $59.13 per hour, depending on experience, location, and employer.

What is a Java Machine Learning job?

A Java Machine Learning job involves developing and deploying machine learning models using Java-based frameworks and libraries. Professionals in this role work on data preprocessing, model training, optimization, and integration into applications. They often use tools like Weka, Deeplearning4j, or Apache Spark MLlib. Strong knowledge of Java, machine learning algorithms, and data structures is essential.

What are the key skills and qualifications needed to thrive in the Java Machine Learning position, and why are they important?

To thrive as a Java Machine Learning professional, you need strong Java programming skills, a solid understanding of machine learning algorithms, and a degree in computer science or a related field. Experience with frameworks such as Weka, Deeplearning4j, or Apache Spark MLlib, along with familiarity with data processing tools and industry-standard certifications, is often required. Problem-solving ability, teamwork, and effective communication are valuable soft skills for success in this role. These skills and qualities are critical for developing robust machine learning solutions, efficiently collaborating with technical teams, and addressing complex business challenges.

What are some common challenges faced by Java Machine Learning professionals on the job?

Java Machine Learning professionals often encounter challenges such as integrating machine learning models into existing Java-based production systems, optimizing algorithms for scalability and efficiency, and ensuring data quality for model training. They may also need to stay current with evolving machine learning libraries and approaches, requiring continuous learning and flexibility. Collaborating with data engineers, software developers, and business stakeholders is common, so strong interpersonal and project management abilities are crucial. Overcoming these challenges is key to successfully deploying high-performing, reliable machine learning solutions that meet organizational needs.
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Java Machine Learning jobs near you
Machine Learning Engineer, Apple Store Online

Machine Learning Engineer, Apple Store Online

Apple

Austin, TX • On-site

Full-time

Posted 7 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Imagine what you could do here! The people here at Apple don't just create products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work...Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things...We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer. You will lead the way on our Online Retail Decision Automation team by researching and developing the next generation of algorithms used to drive the Apple Online experience! This role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimizing Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to be part of a new projects and craft upcoming products that will delight and encourage millions of Apple's customers every day.
To be successful, you need a strong machine learning background, proven software development skills, a love of learning, and to collaborate with cross-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to develop and implement machine learning algorithms. You'll mentor other MLE's and lead an effort to build scalable end-to-end machine learning solutions for our retail customers
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systemsHands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc)Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, Statistics, or Bachelors degree in quantitative field with a focus on AI in coursework
Understanding of machine learning model lifecycle from prototyping, feature engineering, training, inference, deployment, monitoring and continuous improvements via deep analysis)Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architectureExperience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plusExperience with Spark, TensorFlow, Keras, and PyTorch a plusSkilled in communication, problem solving, strategic thinking

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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