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Tokenization Jobs in California (NOW HIRING)

Strong knowledge of transformer architectures, tokenization, and training optimization. * Experience building production ML training pipelines with experiment tracking. * Proficiency in Python ...

Define and optimize payment flows including authorization, capture, settlement, refunds, tokenization, and recurring billing * Review API designs, technical documentation, and integration patterns

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Preferred : • Experience with multi-task learning, Birds-Eye-View (BEV) frameworks, representation learning, or data tokenization is highly preferred. • Familiarity with low-level camera/sensor ...

Our platform supports many of the most notable teams in crypto, with use cases spanning payments, tokenization, and beyond. Built for security, customization, and scalability, Conduit delivers ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Preferred : • Experience with multi-task learning, Birds-Eye-View (BEV) frameworks, representation learning, or data tokenization is highly preferred. • Familiarity with low-level camera/sensor ...

Architect solutions for OAuth 2.0, OpenID Connect, SAML, RBAC/ABAC, MFA, identity federation, KYC, PII tokenization, data vaulting, secure file ingest/scanning, and user/entity deduplication.

Preferred : • Experience with multi-task learning, Birds-Eye-View (BEV) frameworks, representation learning, or data tokenization is highly preferred. • Familiarity with low-level camera/sensor ...

ML Engineer

Aliso Viejo, CA · On-site

$47 - $52/hr

Optimize Elasticsearch/Lucene configurations, including tokenization, stemming, query parsing, and lexical search algorithms (BM25) to work in concert with ML models. * Build and maintain end-to-end ...

Tokenization/token costs * Model selection (GPT, Claude, Gemini, open-source models) * Prompt engineering * RAG * Vector databases * AI agents/MCP * Experience with SMB, dealer networks, or marketing ...

Senior Software Engineer (Card Present)

Irvine, CA · On-site

$131K - $173K/yr

Apply point-to-point encryption (P2PE) and tokenization standards correctly within device integration and transaction processing layers. * Act as a technical resource and mentor for junior and mid ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Preferred : • Experience with multi-task learning, Birds-Eye-View (BEV) frameworks, representation learning, or data tokenization is highly preferred. • Familiarity with low-level camera/sensor ...

Tokenization patterns * PSP integrations * Auth rate optimization * Routing orchestration Frontend * React / Next.js * TypeScript * Component systems * API integration Observability * Prometheus ...

Showing results 41-60

Tokenization information

What is a tokenization?

A Tokenization job typically involves working with financial transactions, data security, or blockchain technology to convert sensitive data into secure, non-sensitive equivalents called tokens. Professionals in this role implement tokenization systems to protect sensitive information, such as credit card numbers or personal data, from fraud or breaches. They may work with compliance teams to ensure adherence to data security regulations. The job often requires expertise in encryption, cybersecurity, and payment processing technologies.

What are some typical challenges faced in a tokenization role?

One of the main challenges in a tokenization role is staying ahead of evolving cybersecurity threats while ensuring that payment and sensitive data remain secure and compliant with industry regulations. Professionals in this role often need to balance the demands of integrating tokenization solutions with existing IT infrastructures and minimizing disruptions to business operations. Working closely with cross-functional teams—including developers, compliance officers, and external vendors—requires strong communication and project management skills. By proactively addressing these challenges, tokenization specialists play a pivotal role in protecting valuable data assets and fostering customer trust.

What are the key skills and qualifications needed to thrive in the tokenization position, and why are they important?

To thrive in a tokenization role, candidates need a solid understanding of payment card industry (PCI) standards, data security protocols, and encryption technologies, often supported by a computer science degree or relevant certifications like CISSP or CISM. Technical proficiency with tokenization platforms, cybersecurity tools, and payment processing systems is typically required. Strong analytical skills, attention to detail, and effective communication abilities are valuable soft skills for collaborating across IT and business teams. These skills are essential for protecting sensitive data, ensuring compliance, and implementing secure, seamless payment solutions.

What are the most commonly searched types of Tokenization jobs in California?

The most popular types of Tokenization jobs in California are:

What job categories do people searching Tokenization jobs in California look for?

The top searched job categories for Tokenization jobs in California are:

What cities in California are hiring for Tokenization jobs?

Cities in California with the most Tokenization job openings:

Infographic showing various Tokenization job openings in California as of August 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 70% Physical, 9% Hybrid, and 21% Remote job distribution.

Senior Lead AI Engineer

Jobtailor

Foster City, CA • On-site

$140 - $190/hr

Other

Posted 17 days ago


Job description

Responsibilities
  • Build and own the end-to-end model fine-tuning pipeline: data preprocessing, training, evaluation, and model registry.
  • Implement and optimize fine-tuning techniques (QLoRA, LoRA, PEFT, full fine-tune) for our training workloads.
  • Design and maintain evaluation harnesses with task-specific benchmarks and automated regression testing.
  • Drive the training iteration loop: analyze results, diagnose failure modes, improve data and configuration.
  • Implement experiment tracking, hyperparameter optimization, and reproducible training workflows.
  • Collaborate on training data strategy with data engineering, including synthetic data generation.
  • Evaluate model quality across safety, accuracy, latency, and cost dimensions.
  • Contribute to model serving architecture and inference optimization.
  • Mentor ML engineers across the team.
Requirements
  • 10+ years of software engineering experience, with 4+ years focused on ML/NLP systems.
  • Hands‑on experience fine‑tuning large language models with parameter‑efficient methods.
  • Strong knowledge of transformer architectures, tokenization, and training optimization.
  • Experience building production ML training pipelines with experiment tracking.
  • Proficiency in Python, PyTorch, and distributed training frameworks.
  • Experience with GPU‑based training infrastructure in the cloud.
  • Strong evaluation methodology: designing benchmarks, measuring quality, detecting regressions.
  • Experience with RLHF, DPO, or other alignment techniques is a strong plus.
  • BS/MS in Computer Science, Machine Learning, or equivalent experience.
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