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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 translate complex research insights into practical applications.
Highest-signal resume keywords
Large Language Model Pre-TrainingSFT, RLHF, RLAIF, DPO TechniquesPython ProgrammingPyTorch or JAXPh.D. in Computer Science or Related Field
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 ResearchModel Training and EvaluationData Synthesis and CurationEvaluation Infrastructure DevelopmentAgentic Systems DesignPublication in ML/AI VenuesMulti-Step ReasoningTool Use in WorkflowsBenchmark DevelopmentResearch Engineering
Soft Skills
CollaborationCommunication of Complex IdeasProject AccountabilityMentoringLeadership
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
- Translate research insights into improvements to enterprise-grade LLMs with research engineering and product teams
- Publish and present original research at top-tier venues
- Mentor and uplevel 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 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
- Annual work-life stipends
- Wellness stipend for gym, massage/chiropractor, personal training, etc.
- Learning and development stipend
- Company-wide off-sites and team off-sites
- Competitive compensation
- Company stock options
- 401k