Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most.
Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.
Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets.
Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology.
We are looking for a commercially-minded research leader to serve as Head of AI Training Research, responsible for delivering measurable client outcomes through applied research excellence. This role sits at the intersection of research and revenue — leading a team of applied researchers, forward deployment engineers (FDEs), and project leads who work in close coordination to ensure every client engagement is backed by rigorous methodology and drives tangible results.
This is not a purely academic role. You will be accountable for the quality, scalability, and commercial impact of our training research practice.
What You'll DoLeadership & Commercial Accountability
- Lead and align a cross-functional pod of applied researchers, FDEs, and project leads around shared client outcome goals
- Own the research practice's contribution to revenue — including supporting pre-sales, scoping engagements, and ensuring delivery quality that drives retention and expansion
- Act as an executive sponsor on strategic accounts, providing research credibility and depth to client relationships
- Build a team culture that is rigorous, fast-moving, and relentlessly focused on client impact
Client Delivery & Applied Research
- Define the applied research frameworks, workflows, and quality standards used across all client engagements
- Ensure applied researchers are translating benchmarking, data, and RL environment work directly into client-specific training solutions
- Partner with project leads to scope engagements accurately, manage research risk, and hit delivery milestones
- Work with FDEs to ensure research outputs are deployable, integrated, and producing measurable model improvements in client environments
Benchmarking
- Oversee the development of benchmarking capabilities used to demonstrate value to clients — pre- and post-engagement performance comparisons, capability gap analyses, and regression tracking
- Ensure benchmark design is tied to client-defined success metrics, not just internal research goals
- Use benchmark outputs as a feedback loop to continuously improve delivery quality across engagements
OTS Data & Data Strategy
- Lead strategy around sourcing, filtering, and deploying off-the-shelf datasets in support of client training objectives
- Build repeatable frameworks for data quality assessment that can be applied efficiently across diverse client use cases
- Identify reusable data assets and pipelines across engagements to improve margins and delivery speed
RL Environment Building
- Oversee the development of RL environments that are purpose-built or adapted for client-specific task performance
- Ensure environments are reproducible and portable across client deployments
- Partner with FDEs and applied researchers to close the loop between environment design and real-world client outcomes
- 8+ years in applied ML or AI research, with at least 3 years leading research or technical delivery teams in a client-facing or revenue-generating context
- Proven track record of translating research capabilities — benchmarking, data curation, or RL — into delivered client value
- Experience working across applied researcher, engineering, and project management functions; comfortable orchestrating cross-functional pods toward a shared outcome
- Strong commercial instincts — able to scope, price, and communicate research work in terms of client ROI
- Deep familiarity with LLM training pipelines, including fine-tuning, RLHF/RLAIF, and evaluation methodology
- Excellent executive communication skills; confident representing the research practice in client conversations and during pre-sales
Nice to Have
- Prior experience at an AI services firm, applied research consultancy, or enterprise AI product company
- Familiarity with data licensing, synthetic data generation, or contamination detection in the context of client data
- Experience building scalable delivery infrastructure (templates, tooling, benchmarks) that improves team output across engagements
Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity.
*Offers will also include bonus + equity
You can find more information about our geographic pay tiers here. During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living.
Bonuses and equity are included in all offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process.
At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI.
We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re okay with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in.
Country Hiring Guidelines:
Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process.
AI Interviewing Guidelines:
Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates.
Accessibility Statement:
We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request. Here is the link the google form: https://docs.google.com/forms/d/e/1FAIpQLScqsu0PCQ0m0lwt-VFeXovNbZxWk0jogv8QI_ciGqZsIbSBjQ/viewform?usp=sharing&ouid=102356854798492362557
Equal Opportunity Statement:
We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.
Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision-making please contact us.
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