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Responsibilities
- Build and maintain trusting relationships with peers and learn the company structure
- Guide local development and actively prototype within one month
- Dive deep into AI and ML use at Sourcegraph and identify improvements
- Develop simulated datasets using Gym style frameworks across Cody use cases
- Experiment with Cody prompts, context sources, and evaluate with offline datasets
- Ship a substantial new feature to end users within one month
- Build out feature computation, storage, monitoring, and serving systems
- Develop distributed training & experiment infrastructure and scale backend services
- Follow and conduct research to contribute to Cody LLM stack
- Own key pieces of the assistant and build ML systems
- Develop a high-QPS inference service with CPU and GPU hardware
- Drive the technical vision and own major ML components and roadmap
Requirements
- 5-8 years of industry experience in ML solutions and data orchestration
- Backend focused ML engineer with experience in end-to-end ML lifecycle
- Deployed ML models to production and developed feature pipelines
- Understanding of ML metrics and user impact
- Working hours overlap with 8am-4pm PT for at least 20 hours per week
Benefits
- Above-average salary with transparency on compensation ranges
- Equity and generous perks & benefits
- Competitive compensation and practical benefits for well-being
