Ai Research Manager/scientist, Model Alignment

AUTODESK CONSTRUCTION CLOUD

Base: $192,600 to $344,850; bonus/equity: annual c...
Fully remote
Phd or equivalent industry experience in machine learning
Proven people management experience for technical teams
Expertise in rlhf, dpo, instruction tuning, and fine-tuning
Autodesk Construction Cloud is seeking an AI Research Manager/Scientist to lead model alignment and post-training efforts. The role combines technical research with people management, requiring hands-on expertise in machine learning and the ability to guide a team of AI scientists while ensuring the reliability and readiness of AI models for production

Job Summary

  • This role sits at the critical intersection of advanced AI research, people leadership, and model readiness, requiring both management and hands-on technical contribution.
  • The successful candidate will lead post-training pipelines including preference optimization methods like RLHF, RLAIF, DPO, and PPO to transform foundation models into reliable systems.
  • Autodesk offers a competitive compensation package including base salaries ranging from $192,600 to $344,850, annual cash bonuses, stock grants, and comprehensive benefits.

Matching Summary

Match Score: 85

Autodesk Construction Cloud is seeking an AI Research Manager/Scientist to lead model alignment and post-training efforts. The role combines technical research with people management, requiring hands-on expertise in machine learning and the ability to guide a team of AI scientists while ensuring the reliability and readiness of AI models for production.

Salary

Base: $192,600 to $344,850; Bonus/Equity: Annual cash bonuses and stock grants included; Benefits: Comprehensive health, financial, and wellness benefits provided

Skills & Requirements

Must-have

  • PhD or equivalent industry experience in Machine Learning
  • Proven people management experience for technical teams
  • Expertise in RLHF, DPO, instruction tuning, and fine-tuning
  • Hands-on experience with large language models and foundation models
  • Strong background in experimental design and evaluation frameworks

Nice-to-have

  • Experience operating in an AI research lab or frontier model organization
  • Background in human-in-the-loop systems and preference learning
  • Familiarity with large-scale training infrastructure and compute cost trade-offs
  • Domain knowledge in Architecture, Civil, or Mechanical Engineering
  • Track record of publishing at top-tier conferences like NeurIPS or ICML

Key Requirements

  • PhD or equivalent industry experience in Machine Learning
  • Proven experience as a people manager of technical research teams
  • Deep expertise in Large Language Models and post-training methods

Work Rights

Not specified

Tailored Resume

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