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Added 9 mins ago
CU
Part-Time Online Course Facilitator: AI/ML Technology and Architecture
Cornell University
Remote, United States
- Part-time
Brings substantial professional experience as a data scientist, machine learning engineer, NLP engineer, AI engineer, or AI/software architect, with a track record of building and deploying…
Added 11 mins ago
TT
Mid/Senior Full Stack AI Engineer
True Talent Solutions Partners
San Francisco, CA
- $180,000 to $250,000 USD / year
- Production experience building and orchestrating LLM agents, including use of an agent framework such as LangGraph, Mastra, or an agent SDK.
Added 13 mins ago
M
Principal Hardware Engineer
Microsoft
WA · CA · OR · NC · TX · Redmond, WA · Mountain View, CA · Hillsboro, OR · Raleigh, NC · Austin, TX · Redmond · Mountain View · Hillsboro · Raleigh · Austin
- $142,800 to $304,200 USD / year
We are looking for a Principal Hardware Engineer to join the team.
Added 13 mins ago
M
Senior Hardware Engineer
Microsoft
CA · WA · TX · NC · OR · Mountain View, CA · Redmond, WA · Austin, TX · Raleigh, NC · Hillsboro, OR · Mountain View · Redmond · Austin · Raleigh · Hillsboro
- $119,800 to $261,000 USD / year
…AI, and agentic workflows. We are looking for a Sr. Hardware Engineer to solve challenging hardware, firmware, software, and system-level problems across Microsoft’s Global Azure Cloud…
Added 39 mins ago
GA
Sr Staff Applications Operations Engineer – Engineering Tools Automation & AI Ops
GE Aerospace
Providence, RI
- $131,000 to $174,000 USD / year
Change agent experienced in Agile delivery (e.g., Scrum, Kanban, SAFe).
Added 44 mins ago
EG
Senior AI Engineer
Eliassen Group
Aberdeen Proving Ground, MD
- $80 to $90 USD / hour
Our client seeks an AI Engineer to support CECOM ASIC in developing and deploying AI/ML models, agentic AI systems, analytics solutions, and automation workflows that drive Army readiness…
Added 58 mins ago
Senior Machine Learning Engineer III ***Raleigh, NC***
RELX INC
Raleigh, NC
Are you looking to develop your Machine Learning Engineer career?
Added 59 mins ago
EG
Staff AI & Data Engineer – Databricks
Eliassen Group
Raleigh, NC
- $80 to $90 USD / hour
Our client is seeking a highly experienced Staff AI & Data Engineer to design and build enterprise-grade data and AI solutions on Databricks. This hands-on role focuses on strengthening the…
Added 1 hour ago
Infrastructure Engineer
Endex
New York City, NY · Los Angeles, CA · Denver, CO · Austin, TX · San Francisco, CA · Chicago, IL
We're looking for an engineer who can make the systems behind Endex reliable, observable and straightforward for the team to operate.
Added 1 hour ago
Forward Deployed Engineer
Endex
New York City, NY · Los Angeles, CA · Denver, CO · Austin, TX · San Francisco, CA · Chicago, IL
We're looking for an engineer who wants to work close to customers and build the software that makes a deployment succeed.
Added 1 hour ago
O
Senior Platform Software Engineer
Oracle
Nashville, TN
- $87,800 to $209,500 USD / year
As a Senior Software Engineer you will own software architecture and development of Oracle's GenAI Agent Platform. You should be both a rock solid coder and a distributed systems…
Added 1 hour ago
EG
Staff AI & Data Engineer – Databricks
Eliassen Group
Montpelier, VT
- $80 to $90 USD / hour
Our client is seeking a highly experienced Staff AI & Data Engineer to design and build enterprise-grade data and AI solutions on Databricks. This hands-on role focuses on strengthening the…
Added 1 hour ago
Enterprise Architecture Manager, Senior Vice President
Citigroup
Irving, TX
…structural impact assessments on core operating platforms to engineer proactive systemic…
Added 1 hour ago
G
Forward Deployment Agentic Engineer
Guidehouse
SAN ANTONIO, TX · HOUSTON, TX
- $70,000 to $116,000 USD / year
Develop reliable agent workflows that use tools, structured outputs, retrieval, and human review where appropriate.
Added 1 hour ago
C
AI Data Engineer
Cognizant
Austin, TX
- $100,000 to $115,000 USD / year
As an AI Data Engineer, you will make an impact by designing, building, and optimizing scalable cloud-native data engineering solutions that enable advanced AI-driven applications and…
Added 1 hour ago
C
AI Data Engineer
Cognizant
Austin, TX
- $100,000 to $115,000 USD / year
As an AI Data Engineer, you will make an impact by designing, building, and optimizing scalable cloud-native data engineering solutions that enable advanced AI-driven applications and…
Added 2 hours ago
TT
Full Stack Engineer
True Talent Solutions Partners
San Francisco, CA
- $230,000 to $300,000 USD / year
- Build product experiences for agent investigations, evaluation workflows, trajectory debugging, verification, and replay.
Added 2 hours ago
CU
Part-Time Online Course Facilitator: AI/ML Technology and Architecture
Cornell University
Remote, United States
- Part-time
Brings substantial professional experience as a data scientist, machine learning engineer, NLP engineer, AI engineer, or AI/software architect, with a track record of building and deploying…
Added 2 hours ago
Senior AI Engineer, AI Safety
NVIDIA USA
Remote, United States
Serving as an AI Engineer on our AI Safety Engineering team, you will have a key and adaptable role in scaling methods to secure and align advanced AI systems. Your early work will center…
Added 3 hours ago
TT
Founding Forward Deployed Engineer
True Talent Solutions Partners
San Francisco, CA
- $180,000 to $230,000 USD / year
Join an early-stage AI customer success software team as a Founding Forward Deployed Engineer. You will work directly with enterprise customers to put AI agents into production, deliver…
Added 3 hours ago
Senior Member of Technical Staff, Platform Engineer (Infra)
Pallet
San Francisco, CA · NY
You could be an Infrastructure Engineer anywhere. Why us?
Added 3 hours ago
Senior Member of Technical Staff, Platform Engineer (Infra)
Pallet
NY · San Francisco, CA
You could be an Infrastructure Engineer anywhere. Why us?
Added 4 hours ago
Principal Software Engineer - Agentic AI & Simulation Automation
Irving, TX
This Principal Engineer role is a hands-on technical leadership position responsible for architecture, critical implementation, engineering standards, cross-team alignment, and mentoring.
Added 4 hours ago
Solution Architect (AWS / AI)
CapNexus
NY
Partner with the Lead Engineer as a peer: you decide the architecture, and they decide the implementation approach.
Added 5 hours ago
EG
Staff AI & Data Engineer – Databricks
Eliassen Group
Harrisburg, PA
- $80 to $90 USD / hour
Our client is seeking a highly experienced Staff AI & Data Engineer to design and build enterprise-grade data and AI solutions on Databricks. This hands-on role focuses on strengthening the…

Closed listing

OKX

Staff Machine Learning Engineer（Risk Intelligence/AI Agent）

San Jose, CA, United States

This opening has closed.

The original listing is kept below for reference.

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Job details

Posting language: English
Posted: Nov 5, 2026

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Original job description

Archived listing. The details below describe a past opening.

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.

Notice:

All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website.

Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX's Candidate Privacy Notice.

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