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Remote Full Stack Machine Learning Engineer Jobs in San Antonio, TX

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Leads the full life cycle of machine learning engineering to include analysis, solution design ...

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... Leads the full life cycle of machine learning engineering to include analysis, solution design ...

AI Engineer III

San Antonio, TX · On-site +1

$120K - $140K/yr

Strong hands-on expertise in machine learning frameworks, agentic AI architecture, and cloud computing platforms * Proven ability to lead technical delivery and mentor engineers in a fast-paced ...

.NET Developer

San Antonio, TX · Remote

$43.50 - $57.50/hr

The Role We are looking for a Senior Full-Stack Developer who builds production software with ... independence on a small remote team in a regulated, security-sensitive environment. Key ...

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Remote Full Stack Machine Learning Engineer information

See San Antonio, TX salary details

$40.1K

$121.6K

$171.8K

How much do remote full stack machine learning engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote full stack machine learning engineer in San Antonio, TX is $121,562.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,100.00 and $142,500.00 per year, depending on experience, location, and employer.

What is a remote full stack machine learning engineer?

A Remote Full Stack Machine Learning Engineer is a professional who designs, develops, and deploys machine learning solutions while working remotely. They handle both the front-end and back-end aspects of machine learning projects, including data preprocessing, model building, API development, and integration with user interfaces or cloud platforms. This role requires expertise in programming, machine learning frameworks, cloud services, and web technologies, allowing them to build end-to-end AI-driven applications from anywhere in the world.

What are the key skills and qualifications needed to thrive as a remote full stack machine learning engineer?

To thrive as a Remote Full Stack Machine Learning Engineer, you need proficiency in programming languages (such as Python or JavaScript), a solid understanding of machine learning algorithms, experience with web development frameworks, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Docker, cloud computing platforms (AWS, GCP), and version control systems (Git) is essential. Strong problem-solving skills, self-motivation, and clear communication are crucial soft skills, especially in remote and cross-functional team environments. These combined skills ensure effective design, deployment, and integration of machine learning solutions in scalable web applications while maintaining productivity in a remote setting.

What are some common challenges faced by remote full stack machine learning engineers, and how can they be addressed?

Remote Full Stack Machine Learning Engineers often encounter challenges such as managing effective collaboration with cross-functional teams and ensuring smooth deployment of machine learning models into production environments. To address these, it's important to establish clear communication channels, regularly participate in virtual stand-ups, and use collaborative platforms such as GitHub and Slack. Additionally, staying organized with version control and thorough documentation helps maintain project transparency and ensures seamless handoffs between backend and frontend development. Proactively seeking feedback and scheduling regular check-ins with team members can further enhance productivity and integration within the team.

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

AspectRemote Full Stack Machine Learning EngineerRemote Data Scientist
Primary FocusDeveloping end-to-end machine learning applications, including backend, frontend, and model deploymentAnalyzing data, creating models, and generating insights without necessarily building full applications
Skills RequiredProgramming (Python, JavaScript), ML frameworks, web development, deployment toolsStatistics, data analysis, visualization, Python/R, SQL
Work EnvironmentCollaborates with developers, data engineers, and product teams in tech-driven companiesWorks with data teams, analysts, and business units in various industries

While both roles involve working with data and machine learning, a Remote Full Stack Machine Learning Engineer builds complete applications with integrated ML models, whereas a Remote Data Scientist focuses on data analysis and model creation without necessarily developing full applications.

What job categories do people searching Remote Full Stack Machine Learning Engineer jobs in San Antonio, TX look for?

The top searched job categories for Remote Full Stack Machine Learning Engineer jobs in San Antonio, TX are:

What cities near San Antonio, TX are hiring for Remote Full Stack Machine Learning Engineer jobs?

Cities near San Antonio, TX with the most Remote Full Stack Machine Learning Engineer job openings:

Senior AI & Machine Learning Engineer

USAA

San Antonio, TX • On-site, Remote

$143K - $273K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


USAA rating

8.2

Company rating: 8.2 out of 10

Based on 263 frontline employees who took The Breakroom Quiz

50th of 171 rated banks


Job description

Why USAA?

At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families.

Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful.

We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs.

The Opportunity

The Senior Artificial Intelligence and Machine Learning Engineer will be part of a dedicated AI engineering team that focuses on developing and implementing AI/ML solutions for all lines of business within USAA. This role provides excellent opportunities to learn and contribute to a variety of exciting areas including sentiment analysis and agentic AI applications to enable USAA to provide best in class service to our members with cutting edge technology. Responsibilities include data preprocessing, model training, building APIs, and building data pipelines.

We offer a flexible work environment that requires an individual to be in the office 4 days per week. This position can be based in one of the following locations: San Antonio, TX, or Plano, TX. Relocation assistance is not available for this position.

What you'll do:

  • Consults with data scientists and business partners on approaches involving ML model development and implementation.

  • Provides technical feedback on ML solutions within technical lead community.

  • Leads the full life cycle of machine learning engineering to include analysis, solution design, data pipeline engineering, testing, deployment, scheduling, application integration, production support, API development, and application integration in support of GenAI applications, ML frameworks/libraires, and ML models.

  • Configure, manage, and set up AI/ML infrastructure components in cloud/on-prem environments for projects and the AI/ML community stakeholders. This includes AWS, GCP, graph databases.

  • Works with architects to influence and define ML model implementation patterns in complex environments.

  • Understand complex model implementation requirements and how to recognize and apply appropriate design patterns throughout solution design and implementation.

  • Designs and implements complex technical solutions for machine learning, artificial intelligence, GenAI, Creates proof of concepts and prototypes on highly complex solutions and presents to leadership to deliver on vision for solution.

  • Assists in setting technical direction for the team and serves as a mentor to team members.

  • Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

What you have:

  • Bachelor's degree; OR 4 years of relevant education and/or experience; and

  • 6+ years of machine learning engineering, data engineering, or software development experience implementing data solutions.

  • Extensive programming experience using Python, SQL, Java etc.

  • Extensive data engineering experience.

  • Experience with end to end delivering of machine learning and AI/GenAI solutions that includes building, integrating, and optimizing data pipelines; curating and modeling the data for various types of consumers/products and their pattern of usage to include data marts, data lake, and operational analytic applications.

  • Experience completing multiple projects leveraging the agile methodology in implementing ML models.

  • Experience leveraging ML Ops principles and implementing automated workflows.

  • Demonstrated technical leadership experience

  • Demonstrated ability to mentor junior members of the technical team in area of expertise.

  • Knowledge of Data Science principles and methodologies.

  • Knowledge of stochastic modeling, machine learning, or other advanced mathematical techniques.

  • Effective communication skills, with the ability to present complex technical concepts to both technical and non-technical audiences.

  • Expert knowledge of at least one cloud platform and relevant components e.g., AWS Sagemaker.

What sets you apart:

  • Programming skills using FastAPI, OpenShift, Snowflake (or any similar platform), Java, etc.

  • Financial services, insurance, banking, or other highly regulated industry experience.

  • Experience mentoring junior developers and providing technical leadership.

  • US military experience through military service or a military spouse/domestic partner

Compensation range: The salary range for this position is: $143,320 - $273,930.

USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.).

Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location.

Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals.

For more details on our outstanding benefits, visit our benefits page on USAAjobs.com.

Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting.

 

USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.


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