ZKML Engineer
Location
Work-from-Anywhere Policy
Employment Type
Full-Time
Department
Engineering
Compensation
$220 - $300K USD +
Offers Equity + Acceleration Options
Additionally, this role is eligible to participate in our accellerated equity plan, culture and benefits program. Equity calculators and financial education programs are included with these programs.
Benefits include, but not limited to: Comprehensive health, dental, vision and mental health coverage, retirement benefits (401K match up to 10%), and flexible PTO, together with fully funded course programs.
Why Colorpay.ai
Colorpay.ai is an Artificially Intelligent Digital Wallet, designed to improve people's lives.
Our symbiotic software combines artificial intelligence, machine learning, holographic cryptography and incentives that have been researched, developed and tested by our expert team. We've found product market fit and are scaling our team very quickly.
Some reasons to join Colorpay.ai are:
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We're on a Mission to improve life for people. These people start with our staff, their families and the people they care for. Our people are well looked after, so they build the things our world needs.
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Exceptional product market fit: We have partnered with the largest AI/ML, finance and legal providers in the world;
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Strategic investors: we've raised a large amount of seed and Series A funding from key global investors.
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World-Class Team: Colorpay.ai is hiring the best talent from DeepMind, Google, Stripe, Tesla, Figma and more.
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Partnerships: Our engineers and researchers work directly with Large Language Model providers including OpenAI, Anthropic, Google Gemini and Meta LLaMA 3.
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"North of Fair" compensation
Role Overview
As an ZKML Engineer on the Engineering team at Colorpay.ai you will join our team at the intersection of advanced cryptography, holographic primitives and machine learning.
In this role, you will lead the design, implementation, and optimization of systems that combine zero-knowledge proofs (ZKPs) with machine learning (ML) models, enabling secure, privacy-preserving AI computation. You’ll work on pioneering use cases such as verifiable inference, model integrity, and on-chain ML verification, helping push the boundaries of what’s possible in decentralized intelligence.
You'll bring strong experience in applied cryptography, particularly zk-SNARKs or zk-STARKs, along with a solid foundation in machine learning, model compression, and efficient inference techniques.
What You'll Do
You’ll contribute to the development of new ZK-friendly model architectures, optimize proving times, and collaborate with protocol engineers, researchers, and ML practitioners to bring trusted, scalable ZKML systems into production. This is a high-impact, technically rigorous role ideal for someone passionate about privacy, trust, and next-generation AI infrastructure.
Working at the frontier of privacy-preserving AI, developing systems that combine machine learning with zero-knowledge proofs (ZKPs) to enable verifiable, confidential computation. Your core responsibility will be to design and implement pipelines that prove the correctness of ML inferences without exposing model parameters or user data. This includes transforming ML models into ZK-compatible formats, optimizing them for proof efficiency, and integrating with SNARK/STARK systems such as Plonk, Groth16, or Halo2. You’ll tackle challenges like circuit design, proof generation, quantization, and adapting neural networks for ZK-friendly operations.
What You Have
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Strong background in applied cryptography, with hands-on experience in SNARKs, STARKs, or zkVMs (e.g., Plonk, Groth16, Halo2, RiscZero).
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Deep understanding of machine learning concepts and architectures, especially model compression, quantization, and inference optimization.
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Proven ability to convert ML models into ZK-friendly formats, such as arithmetic circuits, R1CS, or WASM-based proof environments.
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Proficiency in languages like Rust, Python, and Solidity, with experience contributing to low-level performance-critical code.
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Track record of building or contributing to ZKML pipelines, including benchmarked proofs of inference or ZK-integrated AI applications.
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Experience collaborating on cross-functional teams with cryptographers, ML engineers, and protocol developers in research or production settings.
BONUS POINTS :
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Experience with open-source ZKML tools such as EZKL, Giza, RiscZero, or custom zkDSLs for neural network compilation.
Compensation Range
$220,000 - $300,000 USD
Colorpay.ai is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
