ML Features Solutions Engineer, SambaNova Systems

• Master’s degree or higher in Computer Science, Machine Learning, Electrical Engineering, or related field
• 5+ years of industry experience in ML engineering or applied ML research
• 3+ years of hands-on experience with large language models and transformer architectures
• Expert proficiency in Python and deep learning frameworks: PyTorch (required), TensorFlow, or JAX
• Experience with model optimization techniques: quantization, pruning, distillation, efficient inference
• Strong understanding of LLM inference optimization: KV cache, batching strategies, memory management
• Experience deploying ML models to production at scale
• Track record of translating research concepts into production features

Desirable

• We are seeking an ML Features Solutions Engineer to join our Product and Solution Engineering team, driving the development and optimization of core ML features for enterprise deployment
• This role combines deep ML expertise with hands-on engineering, working at the intersection of ML research and product development to deliver production-grade capabilities to our customers
• This role is critical for accelerating ML feature development and bridging the gap between ML research and product engineering and will be driving the following:
• Core ML Feature Development: You'll drive improvements to ML features including model optimization, inference performance, and feature enhancements
• Production-Ready Solutions: Build and deploy production-ready ML solutions for enterprise customers with focus on reliability and scale
• Research to Product Bridge: Translate ML research innovations into practical product features and customer-facing capabilities
• Cross-Team Collaboration: Work closely with SDK, testing, and customer teams to ensure ML features meet enterprise requirements
• Impact: Accelerates ML feature development and optimization, enabling faster time-to-market for new capabilities while ensuring enterprise-grade quality and performance
• Design and implement core ML features including model optimization, quantization, and inference enhancements
• Optimize model performance for latency, throughput, and memory efficiency on SambaNova hardware
• Develop and improve features such as Function Calling, Structured Output, and JSON mode conformance
• Create end-to-end ML solutions that showcase platform capabilities and accelerate customer adoption
• Convert cutting-edge ML research into practical, deployable product features
• Establish benchmarks and quality standards for ML features in production environments
• Work with SDK team to ensure ML features are properly exposed and documented for developers
• Support enterprise customers implementing advanced ML features in their workflows
• Partner with ML research, platform engineering, and customer teams