FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates deep expertise in large language models and agentic systems, with a strong focus on model training, evaluation, and deployment. Proven ability to lead research initiatives, mentor teams, and publish findings in top-tier ML/AI venues.
Highest-signal resume keywords
Large Language Model ResearchModel Training and EvaluationPython ProgrammingPyTorch or JAXPublication Record in ML/AI Venues
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning ResearchSFTRLHFRLAIFDPOData SynthesisEvaluation MethodologiesAgentic Systems DesignModel Architecture DevelopmentTraining Pipeline Engineering
Soft Skills
CollaborationCommunicationMentoringAccountabilityInnovative Thinking
Certifications & Qualifications
Ph.D. in Computer SciencePh.D. in Machine LearningPh.D. in NLP
Industry Keywords
NeurIPSICLRICMLACLEMNLP
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Lead an independent, high-impact research agenda on large language models and agentic systems
- Own projects from early hypothesis through model training, evaluation, and production deployment
- Design and execute large-scale post-training experiments using SFT, RLHF, RLAIF, DPO, and emerging alignment techniques
- Improve multi-step reasoning, planning, and tool use in enterprise agentic workflows
- Build novel evaluation benchmarks and methodologies for complex, real-world enterprise tasks
- Develop scalable data synthesis and curation pipelines, including LLM-as-judge frameworks, synthetic data generation, and adversarial dataset construction
- Shape WRITER's model architecture and training roadmap
- Work with research engineering and product teams to translate research insights into improvements to enterprise-grade LLMs
- Publish and present original research at top-tier venues
- Represent WRITER in the broader scientific community
- Mentor and develop fellow researchers and engineers
- Report to the VP of AI research
Requirements
What you’ll need- 7+ years of hands-on ML research experience
- Deep expertise in large language model pre-training and post-training
- Ph.D. in Computer Science, Machine Learning, NLP, or a related field, or equivalent demonstrated research experience with a strong portfolio of independent, published work
- Expert-level knowledge of SFT, RLHF, RLAIF, DPO, GRPO, and related alignment and reasoning techniques
- Strong command of Python and PyTorch (or JAX)
- Engineering depth to build and scale training pipelines, evaluation infrastructure, and data synthesis workflows
- Meaningful publication record at competitive ML/AI venues such as NeurIPS, ICLR, ICML, ACL, or EMNLP
- Hands-on experience designing or evaluating agentic systems
- Ability to collaborate across research, engineering, and product and communicate complex ideas clearly
- Ability to challenge conventional wisdom and pursue novel research directions
- Ability to drive projects end-to-end and take accountability for results
Benefits
Comp & perks- Generous PTO, plus company holidays
- Medical, dental, and vision coverage for you and your family
- Paid parental leave for all parents (16 weeks)
- Fertility and family planning support
- Early-detection cancer testing through Galleri
- Flexible spending account and dependent FSA options
- Health savings account for eligible plans with company contribution
- Wellness stipend for gym, massage/chiropractor, personal training, etc.
- Learning and development stipend
- Company-wide off-sites and team off-sites
- Company stock options
- 401k