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.
What You'll Do
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
What We're Looking For
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
Nice to Have
Published research in ML, NLP, or related fields
Experience with retrieval systems and vector databases
Knowledge of cognitive science or human memory research
Background in NLP or information retrieval
Experience with large language models and embeddings
Contributions to open-source ML projects
PhD or Masters in Computer Science, ML, or related field