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Research Machine Learning Federated Learning Jobs in Conway, SC

Nextiny

Entry Level Digital Marketer

Conway, SC · On-site

Conduct keyword research, optimize website content, and assist with SEO strategies. * Create and ... learning, we encourage you to apply! All candidates must be Florida residents.

IQVIA

Senior Data Team Lead (Remote)

Myrtle Beach, SC · Remote

$86K - $217K/yr

Strong understanding of GCP, ICH, and clinical research processes. * Excellent communication and ... Career growth and learning opportunities through mentoring and internal mobility * Inclusive ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Conway, SC

Research Machine Learning Federated Learning information

See Conway, SC salary details

$21.8K

$36.3K

$75.1K

How much do research machine learning federated learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for research machine learning federated learning in Conway, SC is $36,322.00, according to ZipRecruiter salary data. Most workers in this role earn between $27,700.00 and $39,200.00 per year, depending on experience, location, and employer.

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 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 job categories do people searching Research Machine Learning Federated Learning jobs in Conway, SC look for? The top searched job categories for Research Machine Learning Federated Learning jobs in Conway, SC are:
What cities near Conway, SC are hiring for Research Machine Learning Federated Learning jobs? Cities near Conway, SC with the most Research Machine Learning Federated Learning job openings:
Research Machine Learning Federated Learning jobs near you

Early Interventionist (80670)

Kid In Development Services, LLC (KIDS)

Conway, SC

Full-time

Posted 4 days ago

Job description

Essential Job Functions:

  • Maintains a minimum caseload of eighteen (18) clients/families (if full-time).
  • Establishes and maintains professional relationships with families based on trust and respect as support and assistance is provided.
  • Provides early intervention services in the natural environment (i.e., home, daycare, community settings, etc.) to infants and toddlers from birth to three years old with developmental delays or who are at risk for delays in the areas of cognition, language/communication, gross and fine motor, social, and self-help development.
  • Conducts comprehensive family and child assessments that drive individualized service delivery.
  • Provides coaching and support to families and caregivers to enhance child's ability to benefit from learning opportunities in the natural environment.
  • Works with family members and caregivers to create learning opportunities throughout the child's day.
  • Provides families with information on current research and evidence-based practices related to the needs of their child.
  • Takes detailed anecdotal notes and writes reports on child's development and progress.
  • Works with families, caregivers, and members of the IFSP team to develop functional Individualized Family Service Plan (IFSP) goals or outcomes.
  • Monitors IFSPs in accordance with BabyNet policies and procedures.
  • Functions as a member of the child's interdisciplinary team, shares information, and consults with other professionals.
  • Submits accurate and timely routine documentation (clinical service notes) as required by DHHS and KIDS policies and procedures.
  • Ensures client records are kept confidential, accurately maintained, organized, and up to date as required by DHHS and KIDS policies and procedures.
  • Attends all KIDS staff meetings and/or other meetings and trainings as required by the Executive Director or EI Program Manager.
  • Must be willing to travel established territory as needed.
  • Performs other duties as designated by the Special Instruction Supervisor, EI Program Manager, or Executive Director.

MINIMUM QUALIFICATIONS

A Bachelor's degree in one of the following areas:

  1. Education: Early Childhood, Special Education, Early Childhood Special Education, or Elementary Education
  2. Child/Human Development
  3. Interdisciplinary Studies (with approval from BabyNet State Office): with a focus in Early Childhood, Special Education, Early Childhood Special Education, or Elementary Education
  4. Child Life
  5. Communication Disorders (does not require SLP licensure)
  6. Family Studies/Family and Consumer Sciences
  7. Psychology

And (REQUIRED): At least one year of documented experience working with infants and toddlers OR working with children ages birth to 5 years with disabilities.

Must submit an application to the Team for Early Childhood Solutions (TECS) office and meet requirements for the South Carolina Infant-Toddler Credential.

PREFERRED: At least one year of experience with South Carolina's BabyNet Early Intervention Program.

Apply