AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.
About Dragonfly
Dragonfly is a global investment firm focused on the future of money, markets, and intelligence. With origins in crypto and over $3.5 billion in assets under management, we invest in generational companies and protocols across the frontier of finance and technology. We're a team of seasoned VCs, technologists, and markets experts with deep roots in New York, Silicon Valley, and Asia. We've published some of the industry's most widely read research on stablecoins, market structure, decentralized finance, networks, protocol security, and increasingly, the intersection of finance and AI.
This is not a listing for an internal role at Dragonfly. This posting connects you directly with one or more companies in our portfolio that are actively hiring AI/ML Engineers.
What We’re Looking For:
- Comfort operating across the full stack, from model integration to product-facing features
- Building autonomous AI agents, agentic workflows, or agent-to-agent systems
- Familiarity with agentic payments, machine-to-machine transactions, or AI-native economic primitives
- Building and deploying AI systems, LLM-powered applications, or ML pipelines in production
- Working with foundation models, fine-tuning, RAG pipelines, agents, or inference optimization
About the role(s):
Depending on the team, you could be:
- Building and shipping AI-native products and features end-to-end
- Designing and optimizing LLM pipelines, RAG systems, and agentic workflows
- Integrating AI capabilities into crypto-native infrastructure, protocols, or consumer products
- Working on model evaluation, fine-tuning, and inference optimization at scale
- Collaborating with small, high-ownership teams shipping quickly in fast-moving environments
Even if you don't match every point above, we encourage you to apply. There may be other opportunities that fit your skill set.
Process:
- We’ll confidentially match you with portfolio companies aligned with your background, skill set, and interests
- If mutual interest exists between you and a team, we’ll facilitate a warm introduction
- If there isn’t a match today, we’ll keep you top of mind for future opportunities
Compensation
- Early Career: $110,000–$150,000
- Mid: $150,000–$200,000
- Senior: $180,000–$250,000
- Staff/Leadership: $230,000–$330,000
The compensation range reflects variation by seniority, location, and hiring company. Final compensation is confirmed with the specific hiring company.
Submit your information below, and we’ll reach out if there’s a potential fit.
Similar Jobs
Artificial Intelligence • Cybersecurity
Secure SEON’s cloud-based fraud-prevention platform through IAM hardening, infrastructure guardrails, detection engineering, incident response, vulnerability remediation, and threat modeling. Lead ISO 27001, ISO 42001, SOC 2, and PCI DSS assurance programs; automate evidence collection and access reviews; manage customer questionnaires, vendor reviews, policies, risk registers, and regulatory obligations.
Top Skills:
Amazon EksAWSAws IamAws WafCi/CdCloudtrailGitGithub ActionsGuarddutyKubernetesKyvernoLinkerdPythonSecurity HubTerraform
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Leads digital MVP development from investment approval through build, launch, user adoption, and stage-gate transition. Owns product vision, specifications, acceptance criteria, backlog prioritization, delivery planning, scope, risks, dependencies, and evidence-based decisions. Partners with users, engineers, scrum masters, architects, commercial leaders, and sponsors to validate hypotheses, estimate build costs, and deliver viable products.
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Owns the financial integrity and risk-return management of Pfizer’s International Commercial Digital and AI portfolio. The role evaluates business cases, defines KPIs and expected value, audits realized benefits, maintains the benefits ledger, assesses portfolio concentration and risk, runs allocation scenarios, and recommends capital reallocation or investment termination. It partners with measurement, finance, data, and governance teams while presenting evidence-based recommendations to senior Investment Committee stakeholders.
Top Skills:
Competitive IntelligenceData ModelingFinancial ModelingKpi FrameworksPortfolio AnalyticsQuantitative Benchmarking
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


