Senior Solutions Architect - Data Labs
Invisible Technologies4 days ago
Responsibilities
- Equip account teams with technical and research context for client requests and solution decisions.
- Own solution design for new human-data projects and pilots from discovery through handoff and early delivery.
- Interpret ambiguous client requests and translate research objectives into clear, executable approaches.
- Advise on supervised fine-tuning, preference data, RLHF, benchmarks, evaluations, red teaming, multimodal data, coding tasks, agent environments, and emerging methods.
- Design task, annotation, evaluation, quality, validation, data, and expert-profile requirements.
- Develop rough-cut estimates of effort, expert supply, timelines, costs, and overall feasibility.
- Partner with Engineering on expert-facing interfaces, APIs, data exchange, synthetic testing, validation, and technical architecture.
- Prototype or test critical solution elements during discovery and build alignment across internal and client stakeholders.
- Track developments in LLM training, post-training, human data, benchmarks, and evaluation research and turn them into practical guidance.
- Develop reusable solution patterns and best practices for the organization.
Requirements
- Deep interest and strong working knowledge of frontier AI model training and evaluation, including LLM concepts, data modalities, collection methods, and research objectives.
- Exceptional communication, synthesis, stakeholder influence, and judgment in ambiguous client environments.
- Technical fluency in machine learning, data systems, software architecture, APIs, and data flows.
- Commercial judgment and comfort with rough-cut budgeting, expert availability, delivery effort, timelines, costs, and unit economics.
- Experience working across multiple stakeholders or teams in evolving and ambiguous environments.
- A background in computer science, software engineering, machine learning, data science, AI research, technical product, solutions architecture, or a related field is nice to have; equivalent knowledge from independent work or professional experience is welcome.
- Preferred experience includes human-data programs, annotation, model post-training, RLHF, RLVR, evaluations, benchmarks, red teaming, research operations, and collaboration with AI researchers or research engineers.
- Hands-on experience with Python, SQL, APIs, notebooks, lightweight prototyping, or tools and workflows for specialized users is preferred.
- Evidence of serious engagement with AI through professional work, research, open-source contributions, technical writing, independent projects, benchmark participation, or self-directed learning is preferred.
Benefits
- Bonuses and equity are included in full-time offers, with compensation and benefits details discussed during hiring.
- The organization is hybrid, with most positions involving in-office collaboration and location-specific expectations communicated during recruiting.
- Reasonable accommodations are available for candidates with disabilities.
- The company provides an equal opportunity workplace and may use automated decision-making in its hiring process.
About Invisible Technologies
Invisible Technologies builds an enterprise AI operations platform that cleans and labels data, automates digital workflows, and deploys agentic solutions with human-in-the-loop support. It sells subscriptions and managed services that combine software automation with outsourced operations for data transformation and process execution. Founded in 2015 and headquartered in New York, the privately held company cites customers such as Microsoft, AWS, and Cohere across industries.