Member of Technical Staff
Members of Technical Staff at AI labs drive core breakthroughs in model development by owning critical junctures in the training pipeline—from data strategy and synthetic generation through pre-training, mid-training, and post-training optimization. They combine deep research insight with engineering rigor to inject capabilities across reasoning, coding, mathematics, and multimodal understanding, translating empirical findings into measurable improvements that shape what models can fundamentally do. These roles sit at the intersection of research and systems engineering within small, talent-dense teams, where they work cross-functionally to ensure that raw model intelligence becomes aligned, safe, and deployable at scale—balancing theoretical innovation with pragmatic delivery against real-world constraints.
Skills
What companies are looking for in this role.
Designing and implementing large-scale data processing pipelines for machine learning training
Developing methods for data quality assessment, validation, and filtering at scale
Working across the full machine learning pipeline from data preparation through model deployment
Translating research insights into production-grade, maintainable code systems
Building and optimizing training recipes including optimization strategies, learning rates, and hyperparameter tuning
Implementing and debugging distributed training systems across multiple GPUs and nodes
Designing experiments with rigorous methodology and unbiased outcome measurement
Diagnosing and resolving training instabilities, convergence issues, and failure modes
Developing evaluation frameworks and metrics to assess model capabilities and quality
Conducting mathematical reasoning about model training behavior and scaling laws
Optimizing throughput, storage, and compute utilization across distributed systems
Building and maintaining reproducible experiment tracking systems with versioning and metadata management
Building CI/CD and automation tooling to reduce friction in development workflows
Working with real-world robotic systems, simulation environments, and hardware integration
Developing post-training pipelines including supervised fine-tuning, preference learning, and safety alignment
Implementing reinforcement learning and preference optimization techniques for model alignment
Developing synthetic data generation and evaluation strategies for training signal at scale
Designing data mixture strategies and domain adaptation approaches for multi-domain training
Designing and implementing multimodal model architectures spanning vision, language, audio, and video
Adapting foundation models to specialized use cases and customer requirements
Conducting research on frontier topics and publishing findings in peer-reviewed venues
Building high-throughput fine-tuning and evaluation infrastructure for rapid iteration
Developing and validating approaches for assessing and mitigating AI system risks
Designing and executing 3D/4D scene representations and world models for embodied AI
Collaborating across functional teams including researchers, engineers, product, and infrastructure
Taking ownership of end-to-end projects from conception through production deployment
Communicating complex technical concepts clearly to diverse audiences
Prioritizing high-impact work and making pragmatic technical trade-offs under constraints
Technology
The tools and technologies that define this role.
Open Jobs
59 open Member of Technical Staff jobs across 23 companies.
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