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Senior AI Research Scientist

Apex Cognitive Systems
San Francisco
Salary Estimate
USD 180.000 – USD 250.000
Latest
Live Update
26 Mei 2026
Deadline
26 Mei 2027

Job Description

We are looking for a visionary Senior AI Research Scientist to join our elite team at Apex Cognitive Systems. You will be at the forefront of developing next-generation artificial intelligence architectures that solve complex real-world problems. If you are passionate about pushing the boundaries of what is possible in machine learning and want to work in a dynamic, high-performance environment, we want to hear from you.


Why Join Us?

  • Work on cutting-edge Large Language Models (LLMs) and Generative AI.
  • Competitive compensation package including equity options.
  • Flexible remote-first policy with a vibrant office in the heart of San Francisco.

Responsibilities

  • Research & Development: Design, implement, and optimize state-of-the-art deep learning algorithms and neural network architectures.
  • Model Deployment: Translate research prototypes into scalable, production-ready systems using cloud infrastructure (AWS/GCP).
  • Collaboration: Partner with product managers and engineers to define AI requirements and integrate models into consumer-facing applications.
  • Performance Tuning: Continuously monitor, evaluate, and improve model accuracy, latency, and efficiency.
  • Publication: Contribute to academic or industry publications and present findings at top-tier conferences (NeurIPS, ICML, etc.).
  • Mentorship: Guide junior data scientists and engineers, fostering a culture of technical excellence and innovation.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Machine Learning, Statistics, or a related quantitative field.
  • Experience: Minimum 5+ years of professional experience in AI/ML research or applied engineering.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
  • Mathematics: Solid foundation in linear algebra, calculus, and probability/statistics.
  • Tools: Experience with MLOps tools (MLflow, Kubeflow) and version control systems (Git).
  • Communication: Ability to articulate complex technical concepts to both technical and non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Computer Vision Reinforcement Learning MLOps SQL AWS GCP

Ready to Take on This Challenge?

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