Principal Applied AI Researcher - Domain- Specific Models (Dublin, CA)
Dublin, California, United States On-site
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About the role
Articul8 AI is seeking a Principal Research Scientist to define how we build, evaluate, and scale domain-specific models as a durable source of competitive advantage. You will lead research across the full model development lifecycle: domain data strategy, continued pre-training, supervised fine-tuning, post-training, evaluation methodology, and the strategic decisions that determine where Articul8 can create and sustain model superiority in the market. You lead with questions, not answers. You actively seek evidence that contradicts your strategy and revise publicly when warranted. You build an environment where senior researchers feel safe challenging your direction — because that's how the best decisions get made.
What you'll bring
- PhD or MSc in Computer Science, Machine Learning, NLP, or a related field.
- 10+ years in AI/ML research with an exceptional track record of impact — models or systems you built are in production and measurably changed outcomes.
- 4+ years developing LLM-based systems.
- Deep hands-on experience across the full model development lifecycle — continued pretraining, supervised fine-tuning, post-training alignment, and production evaluation.
- You've made the hard calls about when a model is ready to ship and when it isn't.
- You have designed evaluation methodology that goes beyond leaderboard metrics — domain-expert grounded assessment, systematic error analysis, robustness under distribution shift, and readiness criteria for high-stakes deployment.
- Direct experience training or adapting models on large GPU clusters using distributed frameworks (DeepSpeed, FSDP, Megatron-LM).
- You understand the interplay between data mixture, training compute, and model quality at a level that informs strategic decisions.
- Proficient in Python and PyTorch.
- You still write code, review code, and go deep when the problem demands it.
- You have shaped research direction at the organizational level — defining what bets to make, what to stop, and how to allocate research investment across competing priorities.
- People follow your direction because your judgment has been proven right.