Member of Technical Staff

Training and deploying large-scale language and multimodal models on distributed compute infrastructure

Designing and executing model post-training workflows including supervised fine-tuning, preference alignment, and reinforcement learning

Curating, generating, and filtering high-quality training datasets at scale across multiple modalities

Developing robust evaluation frameworks and benchmarks for model capabilities

Optimizing training and inference pipelines for performance and efficiency under production constraints

Translating customer requirements into concrete technical specifications and modeling approaches

Building and maintaining large-scale data processing pipelines and infrastructure

Designing ablation studies and experiments to understand architectural and algorithmic tradeoffs

Implementing custom neural network layers, loss functions, and distributed training code

Architecting multimodal systems that integrate text, vision, audio, and video understanding

Developing safety and alignment techniques for language models and agentic systems

Building systems for model-based planning, reasoning, and inference-time computation

Creating synthetic data generation pipelines to augment training sets

Developing evaluation frameworks that measure real-world model impacts and risks

Designing self-supervised learning approaches for continuous, high-dimensional data

Communicating complex technical concepts to diverse audiences including non-technical stakeholders

Taking end-to-end ownership of projects from requirements through delivery and iteration

Collaborating cross-functionally across research, engineering, product, and customer teams

Translating business metrics and customer outcomes into technical decision-making

Prioritizing pragmatic, measurable outcomes over theoretical novelty

Working autonomously with minimal guidance while maintaining high code quality standards

Mentoring junior engineers and fostering professional growth