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Information Technology 🏢 Full Time ⭐️ Verified

AI Research Scientist

QuantumLeap Labs
Austin
Estimated Salary
USD 180.000 – USD 280.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join QuantumLeap Labs at the forefront of artificial intelligence innovation. As an AI Research Scientist, you'll pioneer breakthrough solutions that will define the technological landscape of 2026. Our Austin-based hub offers a dynamic environment where your expertise in machine learning and neural networks will shape next-generation autonomous systems and predictive analytics platforms.

We're seeking visionary researchers passionate about ethical AI development and scalable algorithms. Collaborate with cross-functional teams to transform theoretical models into real-world applications that impact billions. Enjoy competitive compensation, cutting-edge resources, and the opportunity to publish groundbreaking research in top-tier journals.

Responsibilities

  • Design and implement novel deep learning architectures for next-gen autonomous systems
  • Lead research initiatives in explainable AI (XAI) and ethical algorithm development
  • Develop scalable ML pipelines processing petabyte-scale datasets
  • Collaborate with product teams to translate research into production-ready solutions
  • Author peer-reviewed publications and present findings at industry conferences
  • Mentor junior researchers and contribute to open-source AI frameworks

Qualifications

  • PhD in Computer Science, Machine Learning, or related field (or equivalent experience)
  • 5+ years of experience in neural network architecture design and optimization
  • Expertise in PyTorch/TensorFlow with 100+ model deployments
  • Proven track record of publishing in top-tier ML conferences (NeurIPS, ICML, ICLR)
  • Strong background in distributed computing (Spark, Kubernetes)
  • Proficiency in Python/C++ with high-performance computing experience
  • Understanding of MLOps principles and CI/CD for ML systems

Required Skills

Machine Learning Deep Learning Python TensorFlow PyTorch Neural Networks AI Ethics Distributed Computing MLOps Research

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