River Logo

River

Senior/Staff Machine Learning Engineer

Posted 5 Days Ago
Remote
Hiring Remotely in USA
150K-250K Annually
Senior level
Remote
Hiring Remotely in USA
150K-250K Annually
Senior level
Build and own production ML and LLM systems for onboarding, risk, compliance, and operations. Design models, engineer features from messy data, balance performance and interpretability, integrate with backend training/inference pipelines, write tested code, and partner with product and operations to drive scalable, reliable automation.
The summary above was generated by AI

At River we are building the world’s most trusted financial institution to empower people to take ownership of their financial lives through Bitcoin, the world’s only incorruptible digital money. We believe in a future where every person will have bitcoin savings, and every business will have bitcoin on the balance sheet. We obsessively design and build delightful products that help our clients buy, sell, secure, and use Bitcoin.

We are looking for a Senior/Staff Machine Learning Engineer to build and own machine learning-driven systems that power automation and decision-making across onboarding, risk, compliance, and operations. You will apply ML and LLMs in production to solve real-world problems. Our core stack includes XGBoost, PyTorch, Python, MLflow, Postgres, and BigQuery.

River is growing quickly and has raised more than $50 million from leading investors, including Goldcrest, Kingsway, Polychain, M13, DG, and Valor. We have also released our company's financials and proof of reserves publicly, so all of our clients and employees can verify the robustness and growth of the business themselves.

What you will be doing
  • Design, build, and iterate on machine learning models and LLM-based systems that power critical decisions across fraud, compliance, growth, and operations

  • Work with messy, real-world data to identify signals, build features, and continuously improve model performance

  • Make practical tradeoffs between model performance, interpretability, and operational cost

  • Partner closely with product and operations to identify and solve problems that directly impact experience of hundreds of thousands of clients

  • Contribute to backend systems and data pipelines that support model training and inference (without being primarily an infrastructure role)

  • Write high-quality, tested code and participate in code reviews

  • Take long-term ownership of critical systems as River scales

What we look for in you
  • 4+ years of experience building and applying machine learning models in real-world settings, or comparable research experience

  • Strong intuition for ML concepts and how they apply in practice (i.e., tradeoffs)

  • Experience working on problems involving noisy, imbalanced, or real-world data

  • You take ownership of systems and are comfortable solving ambiguous problems

  • You have strong judgment around correctness, reliability, and operational risk

  • You can translate between technical systems and business/product needs

  • You're excited about what we are building at River

Nice to haves
  • Experience in fraud/risk, fintech, or other high-signal/noise domains

  • Experience with tabular ML and feature engineering-heavy workflows

  • Familiarity with LLM-based systems or applied AI use cases

  • You have worked at a rapidly scaling company

  • Interest in Bitcoin

Location & Salary
  • 100% remote option available within the Americas and Europe, with offices in SF, NYC, and Columbus

  • Salary range between $150,000 - $250,000 based on skills and experience

  • Significant equity stock options

  • Medical, Dental and Vision Benefits

  • Unlimited PTO

  • Parental Leave separate from regular PTO policy

  • 401k

HQ

River San Francisco, California, USA Office

755 Sansome St, Suite 600, San Francisco, CA, United States, 94111

Similar Jobs

3 Hours Ago
Remote
United States
232K-348K Annually
Senior level
232K-348K Annually
Senior level
Artificial Intelligence • Productivity • Software • Automation
As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.
Top Skills: Cloud InfrastructureLlm OpsMl OpsPythonTypescript
Yesterday
Remote or Hybrid
Senior level
Senior level
Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
Perform FP&A work for SMG&A Overheads across DACH & CEE: collect and structure data, consolidate expenditure, run reconciliations and variance analysis in multiple systems, support planning/forecasting and accruals, track optimization projects, deliver ad hoc analyses, ensure controls and collaborate with global finance teams to improve processes.
Top Skills: AdaptiveCmtExcelFitPowerPointSacSAP
Yesterday
Easy Apply
Remote or Hybrid
Easy Apply
Senior level
Senior level
Artificial Intelligence • Cloud • Information Technology • Machine Learning • Software
The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.
Top Skills: AICRMMachine LearningMeddpiccSaaS

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account