• Manage day-to-day project operations in roles such as principal investigator, project director, or task lead. • Lead collaborative project teams by developing timelines, coordinating staff assignments, and ensuring deliverables are completed on time, within budget, and to a high standard. • Identify research problems and design studies to address key questions in applied research contexts. • Apply subject-matter expertise to design and implement relevant, responsive, and impactful research projects. • Develop study designs with aligned research questions, methodologies, and analytic plans. • Lead and contribute to research proposals for federal, state, foundation, and other clients. • Devise and implement innovative solutions to practical challenges in applied research. • Lead data collection and analysis efforts. • Oversee the design and planning of qualitative and/or quantitative data collection tools, such as interview protocols, focus group guides, and surveys. • Supervise field-based data collection activities, including interviews, observations, focus groups, and document reviews. • Conduct or oversee data analysis using appropriate tools and techniques for various data types. • Communicate study progress and findings clearly and effectively. • Prepare reports, briefs, visualizations, and other materials that interpret and present research findings for clients and stakeholders. • Represent the organization professionally in all client interactions. • Communicate effectively, both orally and in writing, with clients, partners, and stakeholders. • Foster and maintain positive, collaborative working relationships. • Manage client and stakeholder relationships with professionalism and awareness of the broader policy and practice landscape. • Contribute thoughtfully and creatively to project teams.

• Set technical direction for core replenishment R&D. • Model complex problems such as inventory decay, promotions, price elasticity, and inventory uncertainty. • Drive fundamental changes to our core system from research through production. • Lead research and development for new product and business challenges. • Mentor scientists and engineers, set standards for experimental rigor.

• Set technical direction for core replenishment R&D — define the modeling roadmap across demand forecasting, inventory optimization, and decision-making policy, and align it with product and business strategy. • Model complex problems such as inventory decay, promotions, price elasticity, and inventory uncertainty, and implement solutions to multi-stage and multi-echelon inventory optimization problems. • Drive fundamental changes to our core system from research through production, writing rigorously tested and scalable code — we are not an analytics team. • Lead research and development for new product and business challenges. • Raise the technical bar across the Intelligence team: mentor scientists and engineers, set standards for experimental rigor, and review designs and results. • Push the boundaries of AI capabilities in both products and scientist workflows.

Role Description This role sits at the heart of Vetto’s mission: using high-quality human data to build AI systems that make the world better. You’ll take raw expert signals and turn it into tangible model improvement, experimenting rapidly and carving new paths in post-training. With full autonomy and no production constraints, you’ll have the freedom to try unconventional ideas and see their impact quickly. Key Responsibilities - Design and run post-training experiments on frontier and open-weight LLMs (SFT, preference-based methods, rubric-driven training) - Translate raw annotation artifacts (multi-step solutions, evaluations, adversarial prompts) into training-ready datasets - Prototype new reward signals beyond pairwise preferences (rubrics, constraints, structured critics) - Analyze failure modes; propose data-centric fixes (sampling, curriculum, counterfactuals) - Build lightweight training/eval pipelines; iterate quickly - Produce short internal memos: what worked, what didn’t, why Qualifications - PhD (or equivalent experience) in ML/AI, applied math, stats, or adjacent - Hands-on experience with LLM post-training (at least one of SFT/DPO/RLHF/RLVR) - Solid Python + PyTorch/JAX; comfortable with training infra basics - Fluent English Preferred Qualification - Worked with rubric-based evaluation or tool-augmented tasks - Experience mixing synthetic and human data - Familiarity with failure analysis and dataset audits Work Model We operate remote-first. We focus on outcomes, not where the work is done. To support flexibility and personal choice, we maintain offices in select locations as an optional resource for the team. Location Flexible (EU-friendly time zones preferred) Type Full-time or long-term contract Equal Employment Opportunity Vetto is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity, age, disability, veteran status, or any other protected characteristic.