Contract

Mathematics Specialist

AI Trainer Project-Freelance

Invisible Technologies

Invisible Technologies

5,001-10,000 employees

AI-assisted BPO and task outsourcing

No salary listed

Remote in USA

Remote

Master's, PhD

Category
AI & Machine Learning (2)
,
Required Skills
LLM
Machine Learning
Cryptography

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Requirements
  • A Master’s or PhD in mathematics or a closely related field is ideal; peer‑reviewed publications, teaching experience, or hands‑on research projects signal fit.
  • You’ll challenge advanced language models on topics like multivariable calculus, cryptography, optimization techniques, machine learning algorithms, mathematical proofs, set theory, combinatorics, and stochastic processes—documenting every failure mode so we can harden model reasoning.
  • On a typical day, you will converse with the model on theoretical and applied mathematics questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improvements to our prompt engineering and evaluation metrics.
Responsibilities
  • Converse with the model on theoretical and applied mathematics questions.
  • Verify factual accuracy and logical soundness of model outputs.
  • Capture reproducible error traces of model responses.
  • Suggest improvements to prompt engineering and evaluation metrics.
Invisible Technologies

Invisible Technologies

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Invisible Technologies combines AI with a global workforce to automate repetitive digital work under a subscription-based model with a dedicated assistant for each client. Clients choose a plan and tasks are automatically routed to AI or human agents, with a transparent portal that shows progress, usage, and billing. The service emphasizes a high-touch, long-term partnership and a predictable, managed workflow, differentiating from traditional outsourcing and big automation providers with its dedicated assistant and visibility. The goal is to streamline operations, boost efficiency, and cut costs by delivering faster, more transparent digital work at scale.

Company Size

5,001-10,000

Company Stage

Growth Equity (Venture Capital)

Total Funding

$107.9M

Headquarters

New York City, New York

Founded

2015

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Simplify Jobs

Simplify's Take

What believers are saying

  • September 16, 2025 funding brought $100 million, valuing Invisible above $2 billion.
  • Revelio Labs counted 4,859 employees in March 2026, with 281 active postings.
  • Management says Invisible stayed profitable for over half a decade and raised expansion capital.

What critics are saying

  • Crowley v. Invisible Technologies, filed November 17, 2023, alleges wage theft and misclassification.
  • Scale AI, Surge AI, Mercor, and Handshake intensify pricing pressure across AI data work.
  • If frontier labs standardize synthetic-data pipelines by 2027, Invisible's human-margin model erodes.

What makes Invisible Technologies unique

  • Invisible combines Neuron, Atomic, Axon, and Meridial into one workflow stack.
  • March 10, 2026 WeCP adds expert-validation libraries for high-precision AI training.
  • Microsoft, AWS, and Cohere use Invisible, signaling enterprise trust and distribution.

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Benefits

Remote Work Options

Performance Bonus

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

4%

2 year growth

7%
Analytics Insight
Jun 11th, 2026
Leading generative AI companies building advanced RAG solutions in 2026.

Leading generative AI companies building advanced RAG solutions in 2026. DataRobot AI, Algoworks, BeyondKey, and Invisible Technologies are among the companies working on RAG-based AI solutions in 2026. They help businesses build smarter AI tools that can search for information and provide useful answers. Published on: 11 Jun 2026, 11:45 am Updated on: 11 Jun 2026, 11:45 am Overview. * DataRobot AI helps businesses build AI tools and use data more effectively. * Algoworks builds custom AI solutions that help companies bring automation into daily work. * BeyondKey creates AI-powered tools that help businesses find and manage information faster. Artificial intelligence has completely changed the business world. Companies are now using AI tools for customer support, data work, internal tasks, and many other daily operations. However, basic AI systems have multiple limitations. They may not always have the latest or most relevant information. This is where RAG solutions step in. Discover more AI technology insights Industry news analysis Crypto market trends Retrieval-Augmented Generation (RAG) allows AI tools to retrieve information from selected sources before generating an answer for users. These systems help businesses to create an AI system that is more useful for their own needs. The use of RAG solutions allows organizations to build smarter search tools, virtual assistants, and workplace apps. Some focus on customer experience, while others use AI to improve employee work. If you are looking for companies working on advanced generative AI and RAG solutions, these are a few names worth considering. DataRobot AI. Location: USA, Boston Founded in: 2012 DataRobot AI helps businesses build AI solutions without overcomplicating the process. The company develops tools that help teams use data, build AI models, and improve everyday decision-making. DataRobot AI is particularly useful for organizations that want an easier-to-use AI solution and don't need a large team to operate it. Its solutions help companies bring AI into their existing work without major changes. Algoworks. Discover more Currencies & Foreign Exchange Machine Learning & Artificial Intelligence Data analytics tools Location: Ramsey, New Jersey Founded in: 2006 Algoworks designs software, offers cloud services, and provides AI solutions. The company helps businesses build custom AI applications that fit their needs. Its RAG solutions enable companies to link AI tools to their own data. Algoworks is highly recommended for developing AI systems that fit the business workflow and not the other way around. Xperiencify Labs. Location: Austin, Texas, USA Founded in: 2019 Xperiencify Labs is working on AI-based solutions to improve digital experiences. The company develops tools to improve users' interaction with technology. This platform is specifically recommended for businesses looking for AI solutions focused on improving user experience. Its approach helps companies create tools that are easier to use. Codete. Location: Kraków, Poland Founded in: 2010 Codete is a software development company providing modern technology solutions. The company helps businesses embed AI features into their applications. Codete is recommended primarily for its ability to combine software skills with AI development. Companies can use the support to make existing apps smarter and provide users with better access to information. BeyondKey. Location: Chicago, Illinois Founded in: 2005 BeyondKey designs AI solutions to help businesses manage information and daily activities. The company is focused on generative AI and business applications. This company offers a practical solution for complex business problems. These are solutions companies can leverage to find information faster and make work easier for teams. Invisible Technologies. Location: San Francisco, California Founded in: 2015 Invisible Technologies helps companies implement technology and automation more effectively. The firm is developing AI tools for different business processes. Its focus on practical use cases is the primary reason why businesses should consider it. With the solution the company provides, organizations can reduce repetitive work and improve how teams handle daily tasks. Why RAG solutions are growing fast. Companies today process enormous amounts of information daily. It can be hard to find the right details fast. That's one of the main reasons companies are moving to RAG solutions. These AI systems allow companies to query their own data for answers. This makes them useful for customer support, employee help desks, and internal search. Another reason for their growth is trust. Companies want AI tools that respond to questions using their own data. RAG reduces errors based on the data sources you select. With AI becoming a bigger part of the workplace, companies are going to be looking for tools that are easy, reliable and helpful. RAG is changing how businesses use AI. Generative AI is no longer simply chatbots. Companies are now looking for AI tools that can understand their data and help them solve their daily problems. Businesses are moving toward smarter AI solutions with the help of companies like DataRobot AI, Algoworks, BeyondKey and Invisible Technologies. Each company focuses differently, ranging from automation to custom AI development. There isn't one AI company that is best for everyone. Some businesses just want better search tools. Others want AI to help them run their day-to-day. What the company wants to do will influence the right choice. As AI grows, businesses are likely to use more RAG solutions to manage information. FAQs. What is RAG in generative AI? Ans: RAG helps AI tools find information from selected sources before answering questions. It makes responses more useful by enabling AI to work with up-to-date, specific information. Why are companies using RAG solutions? Ans: Companies use RAG solutions to manage information better, improve AI responses, and help employees or customers find answers faster without spending extra time searching manually. Which companies provide RAG solutions? Ans: DataRobot AI, Algoworks, BeyondKey, and other AI companies provide solutions that help businesses create AI tools connected to their own information. Can small businesses use RAG-based AI tools? Ans: Yes, small businesses can use RAG tools for customer support, document searches, and simple automation tasks to save time and improve daily work. Is generative AI useful for businesses? Ans: Yes, generative AI helps businesses improve productivity, automate regular tasks, and create better digital experiences for customers and employees.

KnowledgeNile
Mar 11th, 2026
Invisible Technologies Agrees to Acquire WeCP to Strengthen Expert Validation for High-Precision AI Workflows

Invisible Technologies agrees to acquire WeCP to strengthen expert validation for high-precision AI workflows. Business wire India. Invisible Technologies today announced it has entered into an agreement to acquire WeCP, an AI-native technical assessment and intelligence platform known for its rigorously validated evaluation frameworks. As AI systems are deployed across engineering, healthcare, finance, and other complex domains, the quality of the experts shaping those systems has become increasingly critical. High-stakes AI workflows require structured, high-fidelity validation of domain specialists at scale. WeCP brings an AI-native assessment and intelligence platform, which to date has created over two million real-world technical interviews and more than 18,000 targeted domain and role-specific assessment frameworks across engineering, banking, healthcare, finance, and advanced STEM domains. It also has enhanced infrastructure for RL gyms and task simulation. Built over five years of continuous iteration, the platform enables precise evaluation of advanced technical talent. "This acquisition expands our foundation of high-precision AI training," said Matt Fitzpatrick, CEO of Invisible Technologies. "The performance of advanced AI systems depends on trusted human expertise, and WeCP's assessment engine has built one of the most extensively refined technical assessment libraries in the market. By integrating WeCP into Invisible's AI training platform, Meridial, we're raising the bar on precision and speed for expert evaluation across our platform while also accelerating our capabilities in RL gyms and simulated environments." WeCP was founded by NIT Trichy alumni Abhishek Kaushik, formerly of Google, and Mohit Goyal, formerly of Meta, with a vision to modernize technical evaluation. What started as an effort to improve interview question generation evolved into a comprehensive system for measuring real-world skill, reasoning, and domain expertise. Kaushik and Goyal will join Invisible along with several key members of the WeCP team and continue working on their core mission to advance expert assessment infrastructure. "We built WeCP to solve a fundamental challenge: traditional talent vetting does not scale for high-impact, high-precision work," said Abhishek Kaushik, CEO and Co-founder of WeCP. "Joining Invisible allows us to extend our assessment frameworks into advanced AI training environments where rigor and accuracy are essential." About Invisible Technologies. Invisible Technologies is building the platform that makes AI work. It adapts models to each business and adds human expertise when needed - the same approach used to improve models for over 80% of the world's top AI companies, including Microsoft, AWS, and Cohere. Invisible works across 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 over half a decade, was ranked #2 fastest-growing AI company in 2024, and recently raised $100M to advance its platform technology About WeCP. Founded in India by Abhishek Kaushik and Mohit Goyal, alumni of NIT Trichy, WeCP is an AI-native technical assessment platform that designs structured, validated evaluation frameworks to measure real-world expertise across engineering, data science, machine learning, cloud infrastructure, cybersecurity, finance, and advanced STEM roles.

Business Wire
Mar 10th, 2026
Invisible Technologies Agrees to Acquire WeCP to Strengthen Expert Validation for High-Precision AI Workflows

Invisible Technologies agrees to acquire WeCP to strengthen expert validation for high-precision AI workflows. Invisible Technologies today announced it has entered into an agreement to acquire WeCP SAN FRANCISCO & BENGALURU, India-(BUSINESS WIRE)-Invisible Technologies today announced it has entered into an agreement to acquire WeCP, an AI-native technical assessment and intelligence platform known for its rigorously validated evaluation frameworks. As AI systems are deployed across engineering, healthcare, finance, and other complex domains, the quality of the experts shaping those systems has become increasingly critical. High-stakes AI workflows require structured, high-fidelity validation of domain specialists at scale. WeCP brings an AI-native assessment and intelligence platform, which to date has created over two million real-world technical interviews and more than 18,000 targeted domain and role-specific assessment frameworks across engineering, banking, healthcare, finance, and advanced STEM domains. It also has enhanced infrastructure for RL gyms and task simulation. Built over five years of continuous iteration, the platform enables precise evaluation of advanced technical talent. "This acquisition expands our foundation of high-precision AI training," said Matt Fitzpatrick, CEO of Invisible Technologies. "The performance of advanced AI systems depends on trusted human expertise, and WeCP's assessment engine has built one of the most extensively refined technical assessment libraries in the market. By integrating WeCP into Invisible's AI training platform, Meridial, we're raising the bar on precision and speed for expert evaluation across our platform while also accelerating our capabilities in RL gyms and simulated environments." WeCP was founded by NIT Trichy alumni Abhishek Kaushik, formerly of Google, and Mohit Goyal, formerly of Meta, with a vision to modernize technical evaluation. What started as an effort to improve interview question generation evolved into a comprehensive system for measuring real-world skill, reasoning, and domain expertise. Kaushik and Goyal will join Invisible along with several key members of the WeCP team and continue working on their core mission to advance expert assessment infrastructure. "We built WeCP to solve a fundamental challenge: traditional talent vetting does not scale for high-impact, high-precision work," said Abhishek Kaushik, CEO and Co-founder of WeCP. "Joining Invisible allows us to extend our assessment frameworks into advanced AI training environments where rigor and accuracy are essential." About Invisible Technologies Invisible Technologies is building the platform that makes AI work. It adapts models to each business and adds human expertise when needed - the same approach used to improve models for over 80% of the world's top AI companies, including Microsoft, AWS, and Cohere. Invisible works across 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 over half a decade, was ranked #2 fastest-growing AI company in 2024, and recently raised $100M to advance its platform technology. About WeCP Founded in India by Abhishek Kaushik and Mohit Goyal, alumni of NIT Trichy, WeCP is an AI-native technical assessment platform that designs structured, validated evaluation frameworks to measure real-world expertise across engineering, data science, machine learning, cloud infrastructure, cybersecurity, finance, and advanced STEM roles.

Invisible Technologies
Jan 6th, 2026
Invisible Technologies named a Built In 2026 Best Places to Work

Invisible Technologies named a Built In 2026 Best Places to Work. Invisible Technologies Jan 6, 2026 SAN FRANCISCO, January 6, 2026 - Invisible Technologies, the AI software platform for the enterprise, has been recognized by Built In as one of the Best Places to Work in 2026. The annual awards honor employers across the U.S. whose benefits and compensation set the standard for today's workforce. Now in its eighth year, Built In's Best Places to Work program celebrates the companies shaping the future of work. In a rapidly evolving AI-first job market, recognition as a Best Place to Work helps employers stand out as trusted brands when candidates turn to tools like ChatGPT and Google AI Overviews to research where to work next. "Today's candidates discover the companies they want to work for using AI tools," said Maria Christopoulos Katris, Founder & CEO of Built In. "Earning a Best Place to Work award not only signals to candidates that you invest in your people, it's a lever to strengthen how AI search tools understand and represent your company's story." The awards reflect Built In's data-driven approach, evaluating companies based on compensation, benefits, and company-wide culture programs. "This recognition reflects what our team builds every day: high-impact AI systems, real ownership, and a culture that trusts smart people to do meaningful work," says kelly minella, VP of talent acquisition at Invisible. "If you want to be close to the problem, the customer, and the impact, it's a great time to explore Invisible." To learn more about the 2026 Best Places to Work program and view all winners, visit https://employers.builtin.com/best-places-to-work/. About Invisible Technologies. Invisible Technologies is the AI software platform for the enterprise. Their end-to-end AI software platform structures messy data, builds digital workflows, deploys agentic solutions, evaluates and measures impact, and mobilizes relevant human experts. Invisible has trained foundation models for more than 80% of the world's leading AI model providers, including Cohere, Microsoft, and AWS, and has the expertise to customize AI for any industry, function, or use case. Invisible makes AI work in the real world. In 2024, the company reached $134M in revenue and was named the #2 fastest growing AI company on the Inc. 5000. That momentum continued in 2025 with recognition on the Deloitte Technology Fast 500. Book a demo. Invisible Technologies, Inc.'ll walk you through what's possible. No pressure, no jargon - just answers.

Business Insider
Jan 5th, 2026
The CEO of $2 billion AI training startup says that humans will stay involved in data creation for decades

The CEO of $2 billion AI training startup says that humans will stay involved in data creation for decades. Shubhangi goel new follow authors and never miss a story! * Human feedback remains essential for AI training, says Invisible Technologies' CEO. * Synthetic data can't replace humans because there are too many kinds of tasks for AI to accomplish. * Data labeling startups continue to hire specialized workers as tech giants seek high-quality data. Artificial intelligence won't be training AI anytime soon, says the CEO of a data labeling startup. On an episode of the "20VC" podcast released last week, Matt Fitzpatrick, the CEO of Invisible Technologies, said that one of the biggest misconceptions in the AI training industry is that humans won't be needed in a few years. "When I first started this job, the main push back I always got was that synthetic data will take over and you just will not need human feedback two to three years from now," said Fitzpatrick, who joined the startup last year. "From first principles, that actually doesn't make very much sense." Synthetic data refers to data that is artificially created. It is used for training AI or machine learning models, mostly where real data is scarce or can't be used because of privacy concerns. Human feedback, on the other hand, asks real people to filter, rank, and train AI responses. On the podcast, Fitzpatrick said that there are too many kinds of tasks for AI to accomplish in the world, and it would take a long time to do them accurately with language and cultural context in mind. For example, the legal industry contains vast amounts of nonpublic information. Get its newsletter for the inside scoop on today's big stories. "On the GenAI side, you are going to need humans in the loop for decades to come," he said. "And I think that is something that most people are starting to realize." Fitzpatrick was previously a senior partner at McKinsey, where he led QuantumBlack Labs, the firm's AI research and software development arm. Invisible, which raised $100 million in September at a $2 billion valuation, competes with data labeling companies such as Scale AI and Surge AI. These startups have raised billions in the past year as tech giants race to secure the data needed to train their AI models. They hire millions of human contractors, who help teach the models math, science, coding, and characteristics such as humor and empathy. Fitzpatrick joins the CEOs of other data labeling startups in saying that the industry will continue to require human effort. In September, the CEO of Mercor, Brendan Foody, said that the most important aspect of the business was data quality and "having phenomenal people that you treat incredibly well." In July, the CEO of Handshake, a job platform that pivoted into AI training last year, said that humans will still be needed to train AI, but who makes the cut is changing. Garrett Lord said the data annotation industry is shifting from requiring generalists to highly specialized experts, including in math and science. "Now these models have kind of sucked up the entirety of the entire corpus of the internet and every book and video," Lord said on a podcast. "They've gotten good enough where, like, generalists are no longer needed." Read next. Business insider tells the innovative stories you want to know.