Member of Technical Staff, AI Researcher (New Stealth Startup)

Description

The company is an incubation firm that builds and invests in fast-scaling, technology-led businesses in healthcare, cyber, and national security.

The team is a new stealth startup that helps regulated organizations, including healthcare and government groups, turn their internal knowledge into assets that make AI more accurate, reliable, and useful in real workflows.

Customers create, measure, and keep improving AI capabilities that they own and control. The team is made up of builders, researchers, and operators.

This is a Member of Technical Staff, AI Researcher role focused on turning messy, real-world workflows into evaluation frameworks, reinforcement learning environments, and feedback systems that push frontier AI forward.

The work blends research and engineering. You will study how data, evaluations, and feedback shape model behavior, and build the tools needed to test those ideas.

Responsibilities

• Create evaluation frameworks, benchmarks, and methods for frontier language models, AI agents, multimodal models, and reinforcement learning environments
• Build reward models, programmatic verifiers, graders, and other feedback systems that make model behavior measurable and easier to improve
• Run controlled supervised fine-tuning and reinforcement learning experiments that show how datasets affect capability, generalization, and alignment
• Define what makes an evaluation representative of real work and operating environments
• Build systems for collecting high-quality human data, covering expert task design, annotation methods, data-quality signals, and data attribution
• Turn research questions into small, rigorous experiments that produce findings you can act on
• Prototype quickly, assess results, diagnose failure modes, and turn what you learn into better benchmarks, datasets, or systems
• Take promising methods from experiments into scalable, production-quality implementations
• Work with research, engineering, product, and operations to advance a shared technical roadmap
• Contribute to the wider technical community through benchmarks, open-source tools, research, and technical writing

Requirements

• 5+ years of relevant experience in machine learning, artificial intelligence, computer science, data science, software engineering, or a closely related technical field
• You have shown you can work at the intersection of AI research and software engineering
• Strong Python skills and a track record of building reliable, scalable software
• Hands-on work with AI agents, model evaluations, reinforcement learning, post-training, or similar systems
• Solid grasp of frontier AI methods, including benchmarks, evaluation techniques, agent harnesses, post-training approaches, and training-data design
• Experience building or working with reward models, automated verifiers, graders, or other model-feedback systems
• Experience designing evaluations or experiments that measure capability, generalization, alignment, or agent performance
• Ability to turn research prototypes into maintainable, production-quality systems
• Strong analytical, problem-solving, written communication, and technical documentation skills
• You enjoy an open research question and also building the system needed to test it
• You take a builder's approach and aim for measurable, usable results
• You care deeply about how data structure, selection, attribution, and quality affect model behavior
• You can design focused experiments, interpret imperfect or ambiguous results, and turn them into technical decisions
• You move fast without giving up rigor, maintainability, or engineering quality
• You can work in unfamiliar domains and convert real-world workflows into measurable tasks
• You show high agency, sound technical judgment, and a strong sense of ownership
• You explain complex technical concepts clearly to technical and nontechnical stakeholders
• You are comfortable when priorities and technical approaches shift in a fast-moving environment
• You are driven by the purpose and real-world impact of the work, not just access to emerging technology
• An advanced degree in machine learning, AI, computer science, data science, or a related field is preferred but not required. Strong technical, open-source, or published work can substitute, and those candidates are encouraged to apply.
• U.S. citizenship is required

Conditions

The base salary range is $250,000-400,000, plus equity. This is the typical range and depends on experience, skills, and other factors.

Application materials are processed by third-party hiring platforms for verification and fraud checks, and applications flagged for misrepresentation may be declined.

Benefits

• Career track with potential for rapid advancement as the firm grows, based on strong performance
• For full-time roles: 100% employer-paid medical, dental, and vision coverage for you and your family
• Paid maternity and paternity leave of 14 weeks at normal pay
• Unlimited PTO, subject to management approval
• Opportunities for professional development and continued learning
• Optional 401K, FSA, and equity incentives
• Mental health benefits through a third-party provider
• Cost-effective GLP-1 medication solutions through a partner provider
• Benefits may differ by incubation