About the Role
Join our team to build and shape the revolution to supercharge AI assisted coding that transform how enterprise teams validate, implement and ship software. As our first machine learning hire, you'll create NLP systems that understand software specifications, requirements and codebases to create recommendation engines that accelerate development workflows.
Responsibilities
* Architect NLP systems for intelligent spec and code analysis and requirements matching
* Build recommendation engines that pick the correct requirements based on the specs context, project, team setup and more
* Develop semantic search capabilities for enterprise software specs, requirements and code repositories
* Create developer productivity tools powered by machine learning insights from development workflows
* Establish technical architecture and engineering practices for building the ML systems
* Contribute to product strategy by identifying AI opportunities in enterprise software development processes
* Actively participate in building a positive, inclusive, and learning-driven team environment
* Staying current with latest research and ML/AI innovations
Requirements
* 5+ years building production ML systems for technical / enterprise applications
* Experience training, evaluating, and monitoring ML models in production including performance metrics, drift detection, and continuous improvement
* Enterprise software experience including API design, microservices, and cloud deployment
* Code analysis expertise using AST parsing, static analysis, or program synthesis techniques
* Vector databases and embeddings for semantic code search and similarity matching
* Expert-level Python with deep knowledge of ML frameworks (e.g. TensorFlow, PyTorch) and NLP libraries (e.g. spaCy, transformers)
* Developer tooling background with IDEs, CI/CD pipelines, or software analysis platforms (desirable)
* LLM integration experience for code generation, review, or documentation automation (desirable)
* Excellent communication skills in English, both written and verbal
* Ownership mentality with end-to-end feature delivery responsibility
* Proactive approach to proposing and implementing technical improvements
* Capability to evaluate trade-offs and balance scalability, maintainability, and performance