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About the Role

Bridge the gap between cutting-edge research and production systems. Build and implement research prototypes that push the boundaries of memory augmentation and contextual AI.

Responsibilities

Translate research papers and ideas into working prototypes
Collaborate with research scientists to implement novel algorithms
Build experimental systems for memory retrieval and contextual understanding
Optimize research code for production deployment
Design and run experiments to validate research hypotheses
Contribute to research publications and technical documentation
Bridge communication between research and engineering teams

Requirements

3+ years of experience in research engineering or applied ML
Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow)
Experience implementing research papers and prototyping novel ideas
Knowledge of machine learning fundamentals and deep learning
Ability to work independently and manage research projects
Strong problem-solving and analytical skills
Experience with experimentation frameworks and A/B testing
Good communication skills for cross-functional collaboration

Skills

Python
ML frameworks (PyTorch, TensorFlow)
Machine learning fundamentals
Deep learning
Experimentation frameworks
A/B testing
Retrieval systems
Vector databases
Cognitive science
Human memory research
NLP
Information retrieval
Large language models
Embeddings

Experience Level

3+ years of experience

Education Level

PhD or Masters in Computer Science, ML, or related field