ZipRecruiter

Log In

1

Research Machine Learning Federated Learning Jobs in Texas

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Research emerging technologies and recommend enhancements to machine learning delivery, including GenAI, agent-based systems, and AI-assisted development tools. * Present technical recommendations to ...

Crowe LLP

Machine Learning Intern

Austin, TX

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

Crowe LLP

Machine Learning Intern

The Woodlands, TX

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

Crowe LLP

Machine Learning Intern

Houston, TX

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

Crowe LLP

Machine Learning Intern

Plano, TX · On-site

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

Crowe LLP

Machine Learning Intern

Dallas, TX

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX · On-site

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance ...

AtOrchard LLC

Machine Learning Engineer

Austin, TX · On-site

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard ... Experience supporting NOAA, other federal agencies, academic research organizations, or marine ...

7-ELEVEN

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

7-ELEVEN

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

Varsity Tutors

Machine Learning Tutor

Amarillo, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Machine Learning Tutor

San Marcos, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your ...

Varsity Tutors

Machine Learning Tutor

Dallas, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Machine Learning Tutor

Carrollton, TX · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

previous page

Showing results 41-60

All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Texas

Research Machine Learning Federated Learning information

What is a researcher in machine learning federated learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What are the key skills and qualifications needed to thrive as a researcher in machine learning federated learning?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Research Machine Learning Federated Learning jobs in Texas?

For Research Machine Learning Federated Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Research Machine Learning Federated Learning jobs in Texas look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Texas are:

What cities in Texas are hiring for Research Machine Learning Federated Learning jobs?

Cities in Texas with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Machine Learning Developer

Addison Group

Dallas, TX • On-site

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 7 days ago

Job description

Job Title: Machine Learning Developer
Location (city, state): Dallas, Texas - onstie 5x a week
Assignment Type: Direct Hire
Pay: $115,000-$140,000 annually, plus a short-term incentive and long-term incentive.
Benefits: This position is eligible for medical, dental, vision, and 401(k). The company offers fully paid family benefits, a generous 401(k) match, and a competitive paid-time-off program.
Our client is a well-established energy organization with significant operations in the Permian Basin. The company is expanding its artificial intelligence and machine learning capabilities and offers a collaborative environment where employees are trusted to take ownership, contribute ideas, and influence technical direction.
We are seeking a Machine Learning Developer to serve as the first dedicated ML engineering professional within a newly established AI/ML function. This individual will create the MLOps framework, development standards, and platform foundation needed to move machine learning models from experimentation into secure, reliable production environments.
This is a hands-on individual contributor role with significant influence over the organization's future machine learning strategy. The successful candidate will be comfortable setting technical direction, recommending new approaches, and performing the detailed engineering work required to implement those recommendations. This opportunity is ideal for someone who enjoys building programs from the ground up and working in a fast-moving, entrepreneurial environment.
Key Responsibilities:
  • Develop the organization's MLOps strategy, technical standards, reusable workflows, and preferred process for moving models into production.
  • Build and support machine learning solutions within the Databricks environment.
  • Collaborate with data scientists to deploy models using tools such as MLflow, AutoML, Unity Catalog, and Databricks Model Serving.
  • Create automated CI/CD processes for model training, deployment, testing, and promotion between environments.
  • Manage the full model lifecycle, including experiment tracking, model registration, version control, lineage, governance, and user access.
  • Implement monitoring and validation processes for production models, features, and source data.
  • Establish operational visibility for ML systems and assist with troubleshooting and production support when issues arise.
  • Develop standards for data quality, feature reliability, schema validation, and data version management.
  • Produce technical documentation, reference designs, reusable templates, and engineering playbooks.
  • Lead code reviews and share best practices with data science and engineering professionals.
  • Work with business leaders, data scientists, data engineers, and IT teams to define requirements and encourage adoption of shared ML frameworks.
  • Research emerging technologies and recommend enhancements to machine learning delivery, including GenAI, agent-based systems, and AI-assisted development tools.
  • Present technical recommendations to stakeholders and confidently explain or defend a position when viewpoints differ.

Qualifications:
  • Bachelor's degree in computer science, data science, engineering, mathematics, statistics, or a related discipline is required.
  • Three to five years of experience developing, deploying, or supporting machine learning or data-intensive production systems is preferred; candidates with more advanced experience are also encouraged to apply.
  • Hands-on experience with Databricks MLflow and AutoML is required.
  • Advanced Python skills with the ability to create clean, tested, and maintainable production code.
  • Strong SQL capabilities and familiarity with Spark or another distributed data-processing technology.
  • Experience implementing or supporting MLOps practices such as automated pipelines, model deployment, production monitoring, and lifecycle governance.
  • Knowledge of software development fundamentals, including Git, unit testing, CI/CD, and common application design principles.
  • Understanding of widely used machine learning algorithms, model-training methods, evaluation techniques, and hyperparameter tuning.
  • Ability to translate complex technical topics for both technical and nontechnical audiences.
  • Strong analytical, organizational, interpersonal, and problem-solving skills.
  • Ability to work independently, manage competing priorities, and operate with limited supervision.

Apply