• Designing and developing LLM training platform. • Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability. • Improving job scheduling strategies to minimize resource fragmentation.

• Building declarative trading engines so users can compose strategies directly from the UI • Designing automated portfolio construction and rebalancing logic • Integrating with yield vaults, liquidity sources, AMMs, and RWAs • Creating calm, intuitive UX on top of complex onchain primitives • Building scalable infrastructure for long-term asset management

• Design model training and inference workflows with clear versioning, lineage, and promotion criteria where models are part of the system. • Define service responsibilities, interfaces, and data contracts that evolve safely. • Specify behavior under retries, timeouts, partial failures, and dependency degradation. • Choose consistency and durability guarantees that match risk, latency targets, and operational realities. • Design the request path for predictable tail latency and controlled resource usage. • Build and operate high-performance services and APIs that keep authentication reliable, secure, and fast at scale. • Implement distributed services that are safe under concurrency and robust to duplicate and out-of-order events. • Build real-time scoring and decision services with clear input/output contracts and bounded execution time. • Build distributed training pipelines that scale, are reproducible, and produce auditable artifacts. • Build pipelines that move data and model artifacts through validation, promotion, and release. • Define automated quality gates for service changes and releases. • Add checks for data quality, schema/contract adherence, and training-serving consistency where appropriate. • Define acceptance criteria tied to measurable outcomes and production behavior. • Ship changes with staged rollouts and rollback readiness as defaults. • Coordinate multi-service releases with clear cutover and recovery plans. • Use production signals to validate rollouts and trigger rollback when risk is high. • Instrument the full path with metrics, logs, and traces that enable fast detection and diagnosis. • Implement alerting that reflects user impact, not just component health. • Lead incident response for your services, restore service quickly, and communicate clearly during events. • Run post-incident reviews and close follow-ups that measurably reduce recurrence. • Drive reliability work through SLIs, SLOs, and error budgets, and make tradeoffs explicit. • Improve performance and cost through profiling, load testing, and capacity planning. • Raise engineering quality through reviews, standards, and simplification of operationally expensive designs. • Align across teams on interfaces, data contracts, and reliability expectations to reduce coordination friction. • Evaluate new approaches when they materially improve security, performance, delivery safety, or operational simplicity.

• As a Senior Software Engineer, you’ll be responsible for taking SELECT to the next level by architecting and developing new features. • You'll be collaborating with the founders and other engineers, and contribute your ideas to our roadmap and software design. • Creating new cost management features such as forecasts, anomaly alerts and cost allocations to make staying on top of costs a breeze • Developing reusable and robust UI components to make the cost exploration experience as seamless as possible • Building new data visualization capabilities to communicate performance, query timing and efficiency in novel ways • Building data pipelines and dbt models to surface new insights and opportunities to our users • Improving the reliability & performance of our application • Identify the right problems to solve, focusing on meaningful outcomes, and using your experience to make trade-offs that have the highest impact on customers as fast as possible • Take end-to-end ownership for features from start to finish - from inputting into initial design and planning all the way through to implementation, testing, and delivery • Use your expertise to iterate at speed, relying on strong instincts to pragmatically drive the right outcomes while balancing speed and depth. • Set a high bar for collaboration, communication, and sound decision making. From well-written proposals and documentation to clear commit messages and thorough testing.