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Machine Learning Engineer Jobs in Little Elm, TX

Senior ML Engineer

Addison, TX

$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 ...

Showing results 41-60

Machine Learning Engineer information

See Little Elm, TX salary details

$29.1K

$118.9K

$178.6K

How much do machine learning engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for machine learning engineer in Little Elm, TX is $118,880.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,700.00 and $143,100.00 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 Little Elm, TX? The most popular types of Machine Learning Engineer jobs in Little Elm, TX are:
What are popular job titles related to Machine Learning Engineer jobs in Little Elm, TX? For Machine Learning Engineer jobs in Little Elm, TX, the most frequently searched job titles are:
What cities near Little Elm, TX are hiring for Machine Learning Engineer jobs? Cities near Little Elm, TX with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Little Elm, TX as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 100% In-person job distribution, with an average salary of $118,880 per year, or $57.2 per hour.

Software Engineer, Machine Learning (SWE II & SWE I)

Salesforce

Dallas, TX • On-site

$96K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 6 days ago


Salesforce rating

8.1

Company rating: 8.1 out of 10

Based on 58 frontline employees who took The Breakroom Quiz

112th of 242 rated software companies


Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

*IN SCHOOL OR GRADUATED WITHIN THE LAST 12 MONTHS? PLEASE VISIT FUTURE FORCE FOR OPPORTUNITIES*

Slack is looking for a Machine Learning Engineer to craft and implement features, services, API methods, and models to leverage our data to make Slack a fabulous, robust, safe, and valuable product for our users. We work on applications across agentic systems (Slackbot), search, recommendation, and more, but ultimately are looking for engineers excited to drive impact at the forefront of conversational intelligence.

At Slack, the impact can be huge:
  • We have over 10 million daily active users relying on our product.

  • At peak usage, a million messages a minute pass through Slack.

  • During the week, our users spend over a billion minutes a day active in our product.

Machine learning engineers at Slack touch a great variety of parts of our technical stack. At different points, you might find yourself building data pipelines, training recommendation models, fine tuning LLMs, implementing features in our application, or analyzing experiment data. We don't expect everyone to be an expert in everything, but we are looking for candidates with experience in Machine Learning, a strength in at least a couple of these, and who are excited to learn the rest.
This is a practical machine learning team, not a research team. Our goal is to deliver business value with machine learning and data in whatever form that takes. Sometimes that means bootstrapping something simple like a logistic regression and moving on. Other times that means developing sophisticated, finely tuned models and novel solutions to Slack's unique problem space. We are looking for engineers who are driven by driving impact for our business, building great products for our customers, and delivering robust, reliable services with machine learning.

What you will be doing:
  • Leveraging machine learning and artificial intelligence subject matter expertise to drive improvements in the Slackbot experience.

  • Develop ML models supporting ranking, retrieval, and generative AI use-cases.

  • Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features for our large (and growing!) user base.

  • Produce high-quality results by leading or contributing heavily to large multi-functional projects that have a significant impact on the business.

  • Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.

  • Support in the development of sustainable data collection pipelines and management of ML features.

  • Assist our skilled support team and operations team in triaging and resolving production issues.

  • Mentor other engineers and deeply review code.

  • Improve engineering standards, tooling, and processes.

What you should have:
  • Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.

  • Built with common ML frameworks like PyTorch, Tensorflow, Keras, XGBoost, or Scikit-learn

  • Fine tuned LLMs or BERT models.

  • Experience building batch data processing pipelines with tools like Apache Spark, Hadoop, EMR, Map Reduce, Airflow, Dagster, or Luigi.

  • An analytical and data driven mindset, and know how to measure success with complicated ML/AI products.

  • Put machine learning models or other data-derived artifacts into production at scale.

  • Led technical architecture discussions and helped drive technical decisions within the team.

  • The ability to write understandable, testable code with an eye towards maintainability.

  • Strong communication skills and you are capable of explaining complex technical concepts to designers, support, and other specialists.

Nice to have:
  • Expertise in conversational agentic systems.

  • Expertise in retrieval systems and search algorithms.

  • Familiarity with vector databases and embeddings.

  • Knowledge of using multiple data types in RAG solutions including structured, unstructured, and knowledge graphs.

  • Broad experience across NLP, ML, and Generative AI capabilities.

Unleash Your Potential

When you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance andbe your best, and our AI agents accelerate your impact so you cando your best. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what's possible - for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates' resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $128,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $141,200 - $285,800 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

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