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Research Machine Learning Federated Learning Jobs in Texas

HEB

Data Scientist - Demand Forecasting

San Antonio, TX · On-site

$158.10K/yr

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

HEB

Data Scientist - eCommerce

San Antonio, TX · On-site

$158.10K/yr

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

HEB

Data Scientist - eCommerce

San Antonio, TX · On-site

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Additionally, you will analyze the latest research, assess the applicability of emerging deep ... Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ...

HEB

Data Scientist - ML Engineering

San Antonio, TX · On-site

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

HEB

Data Scientist - ML Engineering

San Antonio, TX · On-site

$158.10K/yr

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

Avride

Machine Learning Engineer

Austin, TX

Additionally, you will analyze the latest research, assess the applicability of emerging deep ... Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ...

webAI Inc

Senior Machine Learning Engineer

Austin, TX · On-site

$103.60K - $142.20K/yr

Productionize AI models from research prototypes into scalable, deployable systems used in real ... Experience with edge AI, federated learning, or offline inference systems. * Understanding of AI ...

DISCO

Senior Machine Learning Scientist

Austin, TX

$97.60K - $124.40K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

DISCO

Senior Machine Learning Scientist

Austin, TX · On-site

$97.60K - $124.40K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

ExtendMyTeam

Machine Learning Engineer

Austin, TX

This is a hands-on engineering role focused on production systems, workflow automation, and AI implementation rather than purely research-oriented machine learning work. Responsibilities * Design and ...

webAI Inc

AI Research Scientist

Austin, TX

Design, train, and optimize machine learning models including LLMs, multimodal models, transformers ... Familiarity with privacy-preserving ML techniques such as federated learning * Experience ...

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Research Machine Learning Federated Learning information

What are the key skills and qualifications needed to thrive as a Researcher in Machine Learning Federated Learning, and why are they important?

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 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 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
Data Scientist - Demand Forecasting

Data Scientist - Demand Forecasting

HEB

San Antonio, TX • On-site

$158.10K/yr

Full-time

Posted 14 days ago

Job description

Responsibilities
H-E-B's Corporate Planning and Analysis Team develops and maintains budgets and financial systems while providing current, reliable financial data, analysis, and technical information.
As a Senior Data Scientist, your archetype is a Business Decision Scientist. Your passions include building a framework to stitch cross domains learning and optimizing them toward mission-specific and multi-mission tasks, uncovering ML models causality relationships, creating an enterprise domain-specific reasoning system to boost actionable insights and optimize resources of machine learning process, and orchestrating reusable storytelling methodology to apply toward AI translation.
Once you're eligible, you'll become an Owner in the company, so we're looking for commitment, hard work, and focus on quality and Customer service. 'Partner-owned' means our most important resources--People--drive the innovation, growth, and success that make H-E-B The Greatest Omnichannel Retailing Company.
Do you have a:
HEART FOR PEOPLE... willingness to mentor?
HEAD FOR BUSINESS... skills to serve as technical lead to support decision-making for complex cross-functional business issues?
PASSION FOR RESULTS... ability to generate business-valued questions and data-driven solutions?
We are looking for:
- a creative data storyteller with measurable and predictive business recommendations
What is the work?
Analytics / Design & Development:
- Builds a framework to stitch cross domains learning; optimizes them toward mission-specific and multi-mission tasks
- Serves as expert specializing in AI interpretation and causality; uncovers ML model's causality relationships; builds framework to measure each model's bias, underspecification, and latent drivers with their connections
- Creates an enterprise domain-specific reasoning system to boost actionable insights and optimize the resources of machine learning process
- Orchestrates reusable storytelling methodology to apply toward AI translation
- Applies an inquisitive nature to creating ML / AI transparency to the business
- Applies AI reasoning into business action recommendations
- Applies AI research to accelerate business innovation
What is your background?
- A related degree or comparable formal training, certification, or work experience
- 7+ years of experience in a retail or retail-related decision science role
- Expertise in ML visualization flow
- Expertise in optimizing distributed machine learning in a heterogeneous domain environment
Do you have what it takes to be a Senior Data Scientist at H-E-B?
- Technical knowledge in programming languages: SQL, R, Python, Scala, Java, C/C++
- Technical knowledge in big data / ML optimization: GPU code optimization, Horovod, Spark MLlib optimization, Cython, JNI, Numba
- Technical knowledge in mainstream ML / AI: manifold learning, distributed clustering, graph network, hierarchical model, Bayesian network, deep learning, computer vision, NLP/NLU, reinforcement learning, meta-Learning, federated learning
- Technical skills to consider and apply causal reasoning representation and learning, and human-centric, explainable, responsible AI
- Ability as a creative storyteller and translator between business questions and ML solutions
- Ability to work comfortably with imperfect or incomplete data
- Ability to apply AI reasoning into business action recommendation
Can you...
- Work in a fast-paced retail environment with frequently shifting priorities
- Work extended hours; sit for long periods
08-2021

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