Jobgether-posted 2 months ago
Senior
11-50 employees

As an AI Data Science Research Specialist, you will contribute to cutting-edge research in AI and machine learning by developing novel learning system frameworks and experimental infrastructure. You will collaborate with a team of innovative researchers to implement high-performance data management methods, neural network architectures, and real-time data processing solutions. The role emphasizes hands-on development, from coding and simulation to optimization and visualization of complex systems. You will work on modular, testable code to enable hypothesis-driven experimentation and ensure scalability and reproducibility. This position offers exposure to state-of-the-art AI research, opportunities to influence system design, and the chance to tackle challenging data-driven problems. You will also engage with colleagues across teams to align technical approaches with research goals.

  • Design and implement real-time data management methods, neural network structures, and modular experimental systems.
  • Extend and maintain codebases to support structured learning experiments and simulation infrastructure.
  • Organize internal data structures for system components, including memory modules, experimental runners, and parameter schedulers.
  • Develop structured logging and diagnostic tools to support iterative, hypothesis-driven debugging.
  • Collaborate with other researchers to translate research objectives into practical implementation strategies.
  • Ensure code quality, maintainability, and reproducibility in all experimental and production environments.
  • Ph.D. in Data Science, Computer Science, Software Engineering, or a related field from an accredited university.
  • 5+ years of experience in fundamental data science research and implementation in academic, private, public, government, or military environments.
  • Strong fluency in Python and familiarity with object-oriented and functional programming paradigms.
  • Experience in statistical modeling, frequentist and Bayesian methods, detection theory, and estimation theory.
  • Deep understanding of neural network internals, embeddings, attention mechanisms, and optimization strategies.
  • Knowledge of neuro-symbolic AI systems, simulation frameworks, and recursive dynamics.
  • Experience with parallelization, real-time data management, and visualization methods for structured probabilistic models.
  • Strong analytical, problem-solving, and communication skills; ability to collaborate in evolving, research-driven environments.
  • Curious, fast learner, and comfortable building or modifying systems from scratch.
  • Competitive salary and performance-based incentives.
  • Flexible remote work arrangement within the United States.
  • Comprehensive health, dental, and vision benefits.
  • Retirement plans and financial wellness programs.
  • Paid vacation, sick leave, and parental leave.
  • Professional development opportunities, including mentorship and access to research resources.
  • Supportive and collaborative work environment that encourages innovation and knowledge sharing.
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