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Research Machine Learning Federated Learning Jobs in Texas

Q2

Machine Learning Engineer

Austin, TX · Hybrid

... research and experimentation to advance machine learning capabilities Collaborate with cross-functional teams to integrate AI solutions into production environments Analyze large datasets to extract ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

... research and experimentation to advance machine learning capabilities • Collaborate with cross-functional teams to integrate AI solutions into production environments • Analyze large datasets to ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team ... Strong communicator who can translate complex research findings into actionable decisions for ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

... research and experimentation to advance machine learning capabilities Collaborate with cross-functional teams to integrate AI solutions into production environments Analyze large datasets to extract ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

Striveworks is a leader in Machine Learning Operations for highly regulated industries such as the Department of Defense/U.S. Military. They are seeking a Machine Learning Engineer to be a core ...

Neuralink

Machine Learning Engineer

Austin, TX

Formulate research questions to guide the development of neural networks and signal processing ... for machine learning applications for BCI. * Lead the team by performing at a high standard ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

Research and implement ML algorithms for a variety of business problems * Automate processes for ... Machine learning (ML) algorithms * Predictive modeling and analysis * Data visualization software ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

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 ...

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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:

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

Research Machine Learning Federated Learning jobs near you

Machine Learning Engineer

Q2

Austin, TX • Hybrid

Full-time

Medical

Re-posted 13 days ago

Key responsibilities

  • Design and implement machine learning algorithms and models for various business applications.

  • Collaborate with cross-functional teams to integrate AI solutions into production environments.

  • Analyze large datasets to extract meaningful insights and support data-driven decisions.

Job description

As passionate about our people as we are about our mission.

Why Join Q2?

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology-and we do that by empowering our people to help create success for our customers.


What Makes Q2 Special?

Being as passionate about our people as we are about our mission. We celebrate our employees in many ways through our year-round Q2 ChangeMakers awards program and global moments of recognition and connection. We invest in the growth and development of our team members through ongoing learning opportunities, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun and giving back together. From company-wide volunteer days to events like our Q2 Homecoming Week-featuring learning, community service, and culture-building experiences-we create opportunities to connect, grow, and make an impact.


SUMMARYThe Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning capabilities and support business innovation.Note: Specific tools, technologies, certifications, or travel requirements may be customized by the hiring managerRESPONSIBILITIES Design and implement machine learning algorithms and models for various business applications Conduct research and experimentation to advance machine learning capabilities Collaborate with cross-functional teams to integrate AI solutions into production environments Analyze large datasets to extract meaningful insights and support data-driven decisions Develop scalable machine learning pipelines and systems Maintain up-to-date knowledge of emerging AI and machine learning trends Ensure the quality and performance of AI systems through testing and validationEXPERIENCE AND KNOWLEDGE Bachelor's degree in related field and 5-8 years relevant experience Proven experience in ML model development and deployment Strong knowledge of statistics, optimization, probability theory, and experimental methodologies Proficiency in programming languages such as Python, R, or Java Experience with ML frameworks/libraries (TensorFlow, PyTorch, scikit-learn) Familiarity with cloud platforms and scalable computing resources Strong analytical, problem-solving, and collaboration skills

This position requires fluent written and oral communication in English.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Health & Wellness

  • Hybrid Work Opportunities

  • Flexible Time Off

  • Career Development & Mentoring Programs

  • Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents

  • Community Volunteering & Company Philanthropy Programs

  • Employee Peer Recognition Programs - "You Earned it"

Click here to find out more about the benefits we offer.

Our Culture & Commitment:

We're proud to foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized. And our benefits go beyond healthcare-offering resources for physical, mental, and professional well-being. Click here to find out more about the benefits we offer. Q2 employees are encouraged to give back through volunteer work and nonprofit support through our Spark Program (see more). We believe in making an impact-in the industry and in the community.

We are 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, age, disability, genetic information, or veteran status.


Applicants in California or Washington State may not be exempt from federal and state overtime requirements

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About Q2

Sourced by ZipRecruiter

Industry

Finance and insurance

Company size

1,001 - 5,000 Employees

Headquarters location

Austin, TX, US

Year founded

2004

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