
Machine Learning Research Engineer
Responsibilities
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Operationalize Research: Collaborate with researchers to move models from experimental checkpoints to production-ready systems. Establish patterns for large-scale training, rapid experimentation, and deployment of new architectures.
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Optimize Model Performance: Profile and improve model inference for latency and throughput using quantization, pruning, distillation, and architectural refinements to ensure viable unit economics
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Model Acceleration: Apply optimization techniques (TensorRT, ONNX, vLLM) to accelerate multimodal models including video diffusion, LLMs, and speech models
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Design Data Pipelines: Design and implement efficient pipelines for video data ingestion, preprocessing, and training at petabyte scale using tools like Dagster and Ray.
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Evaluate and Iterate: Build evaluation frameworks to measure model quality, establish benchmarks, and guide continuous improvement of model capabilities.
Requirements
- Production ML: Experience deploying ML models to production. You understand common failure modes and how to address them (resource contention, OOMs, batch optimization)
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Deep Learning Experience: Strong knowledge of PyTorch and modern ML architectures. Experience training and optimizing large models (transformers, diffusion models, or similar).
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Systems Proficiency: Comfortable working with GPUs, debugging CUDA issues, and profiling model workloads to identify compute or memory bottlenecks.
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Data Engineering: Experience building scalable data pipelines for high-bandwidth media processing and training workflows.
Preferred Experience
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Experience with video or audio models in research or production settings
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Familiarity with low-level optimization (CUDA kernels, Triton, custom operators)
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Knowledge of real-time ML systems and latency-critical inference
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Prior work with model compression techniques (quantization, distillation, pruning)
Nuance Labs Key Facts
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$10M seed round backed by Accel, South Park Commons, Lightspeed, and top angels including Synthesia’s former CPO.
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A world-class team of PhDs from MIT, UW, and Oxford with decades of industry experience at Apple and Meta, advancing real-time avatars from cutting-edge research to products used by millions.
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In-person collaboration, 5 days a week at Seattle HQ
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