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Remote Risk Adjustment Coding Jobs in Oakland, CA

OKX

Staff Machine Learning Engineer

San Jose, CA · Remote

... adjustment, account restriction, and other risk mitigation actions. * Work closely with risk ... Apply AI-assisted development throughout the engineering workflow, using LLM coding tools to ...

Swish Analytics

Trading Analyst

San Francisco, CA · Remote

$65K/yr

... 100% Remote Duties: * Manage client risk, ensuring the highest margins on Swish products through +EV decisions * Manage and oversee depth chart accuracy, making time-sensitive adjustments in both ...

Swish Analytics

Trading Analyst

San Francisco, CA · Remote

$65K/yr

... 100% Remote Duties: * Manage client risk, ensuring the highest margins on Swish products through +EV decisions * Manage and oversee depth chart accuracy, making time-sensitive adjustments in both ...

Figma

Security Engineer

San Francisco, CA · Remote

$350K/yr

... code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows ... This is a remote first role. You will partner closely with teams across the company and focus on ...

Quanata

Senior Data Engineer [Remote-US]

San Francisco, CA · Remote

$215K - $300K/yr

When applying for a position online you are at risk of being targeted by malicious actors looking ... Contribute to CI/CD pipelines and infrastructure-as-code practices to ensure reliable, repeatable ...

Brex

Senior GRC Lead

San Francisco, CA · On-site +1

$134K - $185K/yr

What you'll do Brex's Governance, Risk, and Compliance function is at an exciting and pivotal point ... Scale our services by implementing configuration as code via Terraform providers or APIs

Axiad

AI-First SRE/DevOps Engineer

San Jose, CA · On-site +1

$66.75 - $88.75/hr

Mesh translates identity exposure into financial impact, prioritizes risk across human, machine ... US (Remote or HQ Hybrid) Job Type: Full-time Axiad is seeking a skilled AI-First SRE/DevOps ...

Axiad

AI-First SRE/DevOps Engineer

San Jose, CA · On-site +1

$160K/yr

Mesh translates identity exposure into financial impact, prioritizes risk across human, machine ... US (Remote or HQ Hybrid) Job Type: Full-time Axiad is seeking a skilled AI-First SRE/DevOps ...

Bright Vision Technologies

AppSec Engineer

Milpitas, CA · Remote

$100K/mo

AppSec Engineer - Remote Bright Vision Technologies is a technology consulting and software ... Hands-on experience performing code review across at least two major languages. * Deep familiarity ...

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All JobsRisk Adjustment Coding JobsRemote Risk Adjustment Coding JobsRemote Risk Adjustment Coding Jobs in Oakland, CA

Remote Risk Adjustment Coding information

See Oakland, CA salary details

$19

$24

$27

How much do remote risk adjustment coding jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for remote risk adjustment coding in Oakland, CA is $24.69, according to ZipRecruiter salary data. Most workers in this role earn between $20.72 and $26.25 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote risk adjustment coder?

To thrive as a Remote Risk Adjustment Coder, you need a solid understanding of medical coding, anatomy, and healthcare regulations, typically backed by a coding certification such as CPC, CRC, or CCS. Familiarity with coding software, electronic health record (EHR) systems, and risk adjustment models like HCC is essential. Attention to detail, critical thinking, and strong written communication are crucial soft skills for interpreting clinical documentation and ensuring coding accuracy. These skills and qualifications are vital to accurately capture patient risk, ensure compliance, and optimize reimbursement for healthcare organizations.

What is remote risk adjustment coding?

Remote risk adjustment coding is the process of reviewing and assigning medical codes to patient diagnoses and procedures from a remote location, usually at home. The purpose is to ensure that healthcare organizations accurately report the health status of their patients, which affects reimbursement from health plans. Coders use specialized knowledge of ICD-10-CM coding and risk adjustment models, such as HCC (Hierarchical Condition Category) coding, to capture all relevant chronic conditions. This position requires attention to detail, compliance with regulations, and strong analytical skills.

Is remote risk adjustment coding a good career?

Remote risk adjustment coding is a growing field that offers flexibility and the potential for competitive salaries, especially for those with coding certifications and knowledge of healthcare documentation. It requires attention to detail, understanding of medical records, and proficiency with coding software. The demand for remote coders is increasing as healthcare organizations seek efficient ways to manage risk and compliance.

What is the difference between Remote Risk Adjustment Coding vs Remote Medical Coding?

AspectRemote Risk Adjustment CodingRemote Medical Coding
CertificationsRHIA, RHIT, CPC, CCSCPC, CCS, CCS-P
Work EnvironmentHealthcare organizations, insurance companiesHospitals, clinics, insurance companies
Industry UsageHealth insurance, risk adjustment programsMedical billing, claims processing

Remote Risk Adjustment Coding focuses on analyzing patient data for insurance risk assessments, requiring specific risk adjustment certifications. Remote Medical Coding involves coding diagnoses and procedures for billing purposes. While both roles require coding certifications, Risk Adjustment Coding emphasizes risk analysis within insurance, whereas Medical Coding centers on billing accuracy.

How does working remotely as a risk adjustment coder impact collaboration with healthcare teams and ongoing professional development?

As a remote Risk Adjustment Coder, you'll often collaborate with clinical staff, auditors, and other coders through secure digital platforms and regular virtual meetings. While remote work offers flexibility, it also means that proactive communication is essential to ensure accurate coding and compliance with regulations. Many organizations provide virtual training sessions, access to coding forums, and ongoing education to help you stay updated on industry changes and coding standards. Building relationships with your team and participating in online professional communities can further support your growth and help overcome the isolation that sometimes comes with remote work.

What are popular job titles related to Remote Risk Adjustment Coding jobs in Oakland, CA?

For Remote Risk Adjustment Coding jobs in Oakland, CA, the most frequently searched job titles are:

What job categories do people searching Remote Risk Adjustment Coding jobs in Oakland, CA look for?

The top searched job categories for Remote Risk Adjustment Coding jobs in Oakland, CA are:

What cities near Oakland, CA are hiring for Remote Risk Adjustment Coding jobs?

Cities near Oakland, CA with the most Remote Risk Adjustment Coding job openings:

Remote Risk Adjustment Coding jobs near you
Infographic showing various Remote Risk Adjustment Coding job openings in Oakland, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $51,364 per year, or $24.7 per hour.

Staff Machine Learning Engineer

OKX

San Jose, CA • Remote

Full-time

Re-posted 3 hours ago

Job description

Who We Are

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.

OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. 

Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.

OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.

About The Opportunity
Building machine learning systems for risk at a global crypto exchange is fundamentally different from conventional ML engineering. The data spans on-chain activity, fiat deposits and withdrawals, trading behaviour, account access patterns, device intelligence, identity information, and customer interactions-signals that very few organizations can analyze together.
The problems are complex, adversarial, and constantly evolving. Models must identify emerging fraud patterns, scams, account takeovers, payment abuse, and other forms of financial risk while minimizing disruption to legitimate customers. Success is not measured only through offline model metrics. It is measured through prevented losses, improved approval rates, reduced false positives, faster investigations, and more reliable customer experiences.
This role sits within a multidisciplinary risk team of machine learning engineers, data scientists, risk strategy specialists, analytics engineers, product managers, and operations teams. You will work across the full ML lifecycle-from problem formulation, feature engineering, and model development to real-time deployment, monitoring, experimentation, and continuous iteration.
You will also help shape how AI is used across the risk organization. LLM-assisted development, automated model workflows, AI-powered investigations, and intelligent review agents are part of the team's daily work. We are looking for engineers who already use these tools effectively and can help establish safe, scalable, and production-ready AI practices.
 
What You'll Be Doing
  • Design, build, and deploy machine learning models for risk use cases such as payment fraud, account takeover, scam detection, deposit and withdrawal risk, promotional abuse, customer risk assessment, and transaction monitoring.
  • Own production ML systems end to end, including feature pipelines, training workflows, model serving, decision integrations, monitoring, alerting, drift detection, retraining, and incident response.
  • Partner with risk strategy and product teams to translate models into effective production controls, including approval, rejection, review, cooldown, limit adjustment, account restriction, and other risk mitigation actions.
  • Work closely with risk operations teams to understand investigation workflows, incorporate reviewer feedback, improve model explainability, and continuously refine labels and training data.
  • Apply AI-assisted development throughout the engineering workflow, using LLM coding tools to accelerate implementation, testing, debugging, analysis, and documentation while maintaining appropriate security and review standards.
  • Develop AI-powered risk capabilities such as investigation agents, case summarization, evidence collection, review recommendations, alert triage, suspicious-entity mining, and automated decision support.
  • Take research-stage models into reliable production systems by validating feature logic, reviewing data quality, addressing latency and scalability constraints, and ensuring consistency between offline training and online inference.
  • Ensure models and decision systems are explainable, traceable, and well documented so that model outputs can be understood by risk operations, product stakeholders, internal governance teams, and regulators where applicable.
  • Design, build, and deploy LLM-based agents for risk operations and investigation workflows, including case triage, evidence retrieval, transaction analysis, alert summarization, review recommendations, and automated action orchestration.
  • Develop production-grade agent architectures using tool calling, retrieval-augmented generation, workflow orchestration, structured outputs, memory, guardrails, and human-in-the-loop controls.
  • Build evaluation frameworks for LLM agents, measuring factual accuracy, task completion, decision consistency, latency, cost, reviewer acceptance, and operational impact. Ensure LLM agents operate safely in a regulated risk environment by implementing permission controls, audit logs, data privacy protections, prompt and tool security, fallback mechanisms, and clear escalation paths.
What We Look For in You
  • Significant professional experience in machine learning engineering, applied data science, or a closely related field, with a strong record of taking models from prototype to production. Scope and level will be calibrated based on experience.
  • Strong Python skills and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, XGBoost, LightGBM, or scikit-learn.
  • Strong knowledge of applied machine learning fundamentals, including supervised learning, anomaly detection, representation learning, class-imbalanced modeling, model calibration, and evaluation under changing data distributions.
  • Demonstrable fluency with AI-assisted engineering. You regularly use LLM coding tools, have built AI-integrated workflows or applications, and understand both the productivity benefits and the security, reliability, and governance risks.
  • Familiarity with model explainability techniques such as SHAP, feature attribution, reason-code generation, and model scorecards.
  • Hands-on experience designing and deploying production LLM agents, including agentic workflows, tool calling, retrieval-augmented generation, prompt and context management, structured output generation, and multi-step task orchestration.
  • Experience integrating LLM agents with internal systems, APIs, databases, search tools, case-management platforms, or decision engines to automate complex operational workflows.
  • A strong understanding of LLM-agent evaluation and reliability, including hallucination control, grounding, observability, permissions, failure handling, human review, latency, and cost optimization.
  • Experience building AI agents for fraud, risk, compliance, customer operations, cybersecurity, or other high-stakes domains is a meaningful advantage.
  • Strong communication and collaboration skills, with the ability to work effectively with engineers, data scientists, risk specialists, product managers, operations teams, and legal or compliance stakeholders.
OKX Statement
The base salary range for this position is $214,666 to $321,999. The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via Okcoin and OKX internal or external careers site.
 
OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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