Senior Solutions Architect - Data Labs
About this role
Invisible makes AI work by building an end-to-end platform that structures messy data, automates digital workflows, deploys agentic solutions, and integrates human expertise. The company's Data Lab works with leading AI companies to design and deliver the human data that advances model capabilities and measures performance.
As a Senior Solutions Architect, you will sit at the intersection of machine learning research, human data, product thinking, and client partnership. You will work with client researchers and internal account teams to translate open-ended, underspecified model development problems into scalable programs with sound methodology. Your responsibilities include leading solution design for new opportunities and pilots, advising on methodology across supervised fine-tuning and evaluation, and partnering with engineering to define expert-facing interfaces and technical architecture.
This role suits someone with a deep interest in how frontier AI models are trained and evaluated, exceptional communication skills, and strong commercial judgment. You will help determine how novel human-data programs should work before there is an established playbook, shaping how Invisible approaches the field while working directly with top AI companies.
What you will do
- Equip account teams with the technical and research context needed to understand client requests and make sound decisions.
- Own the solution design of new human-data projects and pilots from early discovery through the transition into execution.
- Work directly with client research and program management stakeholders to turn ambiguous requests into clear and executable approaches.
- Advise on methodology and best practices across supervised fine-tuning, preference data, RLHF, benchmarks, evaluations, and red teaming.
- Shape task design, annotation workflows, quality strategies, and data structures while balancing research value and feasibility.
- Build rough-cut estimates of effort, expert supply, timeline, and cost to test feasibility and shape viable proposals during early scoping.
- Partner with Engineering to define technical architecture, workflows, APIs, and validation mechanisms required for collections.
What you need
- Demonstrable interest and active tracking of how frontier AI models are trained, improved, and evaluated.
- Strong working knowledge of LLM training and evaluation concepts across various data modalities and research objectives.
- Exceptional communication skills to listen, clarify underspecified requests, and influence diverse stakeholders.
- Sound judgment to constructively challenge assumptions while maintaining project momentum and client trust.
- Technical fluency in machine learning, data systems, software architecture, and APIs to collaborate with engineers.
- Commercial judgment with comfort in budgeting and weighing research ambition against delivery effort and cost.
- Experience working across multiple stakeholders or teams in ambiguous environments with evolving requirements.
Nice to have
- A background in computer science, software engineering, machine learning, data science, AI research, technical product, solutions architecture, or a related field.
- Direct experience with human-data programs, data annotation, model post-training, RLHF, RLVR, evaluations, benchmarks, red teaming, or research operations.
- Experience partnering directly with AI researchers, research engineers, or technical program managers.
Skills and tech stack
Questions candidates ask
What is the location policy for this role?
This position offers hybrid work options based out of London, New York, or the San Francisco Bay Area.
What team will I be working in?
You will be embedded within an account team working with a major frontier AI lab, specifically part of Invisible's Data Lab.
What will I actually work on day-to-day?
You will lead solution design for new opportunities and pilots, translate ambiguous client requests into executable approaches, and advise on methodology across supervised fine-tuning, preference data, and evaluations.
The application is on the official Invisible Technologies careers page.
Apply on company site