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Principal Research Engineer, Model Training & Post-Training

Inflection AI· Engineering
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Palo Alto, California$400k - $550kPosted 3mo ago

About the role

Hands-on technical leader responsible for the model-improvement loop from data and training through evals, post-training, release criteria, and production feedback. Sits at the intersection of research, production engineering, and model release to ship measurably better models for users.

Responsibilities

  • Own the model-improvement roadmap across capability, reliability, emotional intelligence, tool use, safety, latency, cost, and enterprise readiness.
  • Lead training and post-training strategy, including supervised fine-tuning, RLHF, DPO, GRPO, RLAIF, reward modeling, preference optimization, tool-use fine-tuning, distillation, synthetic data, and related methods.
  • Drive model architecture and optimization decisions across modern transformer-based and hybrid architectures, including both training-time and inference-time performance.
  • Lead large-scale training efforts on distributed GPU clusters, including systems operating at the scale of 1,000+ GPUs.
  • Define and execute data strategy across data curation, mixture design, deduplication, decontamination, human-in-the-loop pipelines, preference data, evaluation data, synthetic data, and production feedback loops.
  • Build and improve evaluation and release-quality systems, including model evals, quality gates, regression detection, release criteria, model-readiness reviews, and post-release monitoring.
  • Partner closely with infrastructure and research engineering teams to improve distributed training reliability, checkpointing, fault tolerance, observability, reproducibility, and cost-performance tradeoffs.
  • Debug and improve model behavior across the full stack: data, training, post-training, evaluation, infrastructure, product integration, and production feedback.

Qualifications

  • Experience leading, or serving as a principal contributor to, large-scale LLM, multimodal, or foundation-model training or post-training programs.
  • Deep experience with transformer-based models, hybrid architectures, modern deep-learning frameworks, and distributed training systems.
  • Strong practical experience with post-training and alignment methods such as SFT, RLHF, DPO, GRPO, RLAIF, reward modeling, preference optimization, tool-use fine-tuning, or related approaches.
  • Experience operating or partnering on large-scale training infrastructure, ideally including GPU clusters at the scale of 1,000+ GPUs.
  • Strong systems instincts around throughput, cost, reliability, observability, debugging, checkpointing, reproducibility, and fault tolerance.
  • Excellent judgment around data quality, evaluation design, model regressions, release readiness, and production model behavior.
  • Ability to balance research ambition with product pragmatism, user impact, and operational discipline.
  • Experience leading senior technical teams while continuing to contribute directly to technical decisions and implementation.
  • PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent practical experience.

Skills

Required:Model training and post-training strategyTransformer-based models and hybrid architecturesDistributed training on large GPU clustersEvaluation and release readinessData strategy and data quality

Benefits

  • Robust medical, dental and vision options with employer contributions for HSA, FSA and DFSA
  • 401k matching program
  • Flexible Time Off, 10 paid holidays, 5 days sick leave
  • Parental, Medical and Family care leave
  • Generous cell-phone, wellness and office set up stipends
  • Support of country-specific visa needs for international employees living in the Bay Area
Last updated Jul 8, 2026. Interested? Apply on the company site.

About Inflection AI

Pi, your personal AI

Inflection AI is pioneering the future with human-centered, emotionally intelligent AI that transforms interactions from transactional to reltational, creating enduring value for individuals and enterprises alike.

AIemotional intelligencehuman-centered interactionliquid-ai-recruiting-target
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