Applied Methods
~The MetaResearch & ScienceMember of Technical Staff

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.

$ titles --canonical
Member of Technical StaffMTSSenior Member of Technical StaffStaff Member of Technical StaffMember of Technical Staff - Pre-TrainingMember of Technical Staff - Post-Training
54open jobs
22companies hiring
$02

Skills

What companies are looking for in this role.

$ skills --core

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

95%

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

92%

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

88%

Developing robust evaluation frameworks and benchmarks for model capabilities

85%

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

82%

Translating customer requirements into concrete technical specifications and modeling approaches

78%

Building and maintaining large-scale data processing pipelines and infrastructure

75%

Designing ablation studies and experiments to understand architectural and algorithmic tradeoffs

72%

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

70%
$ skills --emerging

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

72%

Developing safety and alignment techniques for language models and agentic systems

68%

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

65%

Creating synthetic data generation pipelines to augment training sets

62%

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

60%

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

58%
$ skills --soft

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

88%

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

85%

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

82%

Translating business metrics and customer outcomes into technical decision-making

72%

Prioritizing pragmatic, measurable outcomes over theoretical novelty

70%

Working autonomously with minimal guidance while maintaining high code quality standards

68%

Mentoring junior engineers and fostering professional growth

65%
$03

Technology

The tools and technologies that define this role.

$ tech --language
Pythonvery high
$ tech --framework
PyTorchvery high
JAXhigh
Apache Sparkmoderate
Raymoderate
FLUXlow
Stable Diffusionlow
$ tech --platform
CUDAhigh
Kuberneteslow
$ tech --tool
Dockermoderate
NCCLmoderate
$ tech --concept
GPUvery high
Diffusion modelshigh
Distributed traininghigh
Evaluation benchmarkshigh
Inference optimizationhigh
Reinforcement Learninghigh
Synthetic data generationhigh
Transformershigh
Vision-Language Modelshigh
Attention mechanismsmoderate
Model compressionmoderate
Multi-task learningmoderate
Retrieval-Augmented Generationmoderate
Speech-to-textmoderate
Text-to-speechmoderate
Tokenizationmoderate
Geminilow
Groklow
LFM2.5-Audiolow
$04

Open Jobs

54 open Member of Technical Staff jobs across 22 companies.

Cognition3d
Research, Mid-Training
San Francisco Bay Area·Research & Science
Cognition3d
Research, Post-Training Data
San Francisco Bay Area·Research & Science
Perplexity1w
Member of Technical Staff - AI Policy and Strategic Initiatives
San Francisco·Research & Science
Mistral AI1w
Applied Scientist / Research Engineer - Multimodal (Come to Singapore)
Paris·Research & Science
Liquid AI1w
Member of Technical Staff - Post Training, Applied (Vision)
San Francisco·Research & Science
Liquid AI1w
Member of Technical Staff - Applied ML, RecSys
Boston·Research & Science
Liquid AI1w
Member of Technical Staff - Post Training, Applied (Audio)
San Francisco·Research & Science
xAI2w
Member of Technical Staff - Model Training
London, UK·Research & Science
DeepMind2w
Research Engineer, Frontier Safety Risk Assessment
London, UK; New York City, New York, US; San Francisco, California, US·Research & Science
xAI2w
Member of Technical Staff - International Government
London, UK·Research & Science
xAI2w
Member of Technical Staff - Government (Cleared)
Los Angeles, CA; Palo Alto, CA; Washington, D.C.·Research & Science
xAI2w
Member of Technical Staff - Government
Washington, D.C.·Research & Science
xAI2w
Member of Technical Staff - Reasoning
London, UK·Research & Science
xAI2w
Member of Technical Staff - Multimodal Understanding
New York, NY; Palo Alto, CA·Research & Science
xAI2w
Member of Technical Staff - Grok Main Model
Palo Alto, CA·Research & Science
xAI2w
Member of Technical Staff - Model Training
Austin, TX; New York, NY; Palo Alto, CA; Seattle, WA·Research & Science
xAI2w
Member of Technical Staff - Voice Model
Palo Alto, CA·Research & Science
xAI2w
Member of Technical Staff - Ads
Palo Alto, CA·Research & Science
Black Forest Labs2w
Member of Technical Staff - Image / Video Generation
Freiburg (Germany)·Research & Science
Cohere2w
Member of Technical Staff, Safety for Agents
London·Research & Science