Machine Learning Engineer
Machine Learning Engineer at FINNY AI — New York City, US
- Company: FINNY AI
- Location: New York City, US
- Employment type: FULL_TIME
- Salary: USD 180000–200000 / year
- Posted: 2026-07-17
About this role
About FINNY
FINNY is a growth platform for financial advisors. We are on a mission to make great financial advice easier to find. Today, access to quality financial guidance is limited, not because advisors don’t exist, but because the right connections are hard to make when it matters. We’re fixing that with AI-powered tools that help advisors find, engage, and retain the clients they can genuinely help.
We’ve raised a 4.3 million pre-seed from Y-Combinator in S24 and now $17M Series A led by Venrock. We work with firms across the wealth management ecosystem, and have been recognized as a leader in fintech innovation—winning #1 at the Morningstar Fintech Showcase and being featured across the industry.
We’re based in Chelsea, NYC, building fast and ambitious systems at the intersection of data, AI, and real-world wealth services.
About the Team
Being a Machine Learning Engineer at FINNY means owning the models that power search, matching, ranking, recommendations, data and intelligent automation across the product. This is a model first role. While you’ll work with real production data and pipelines, your primary impact comes from designing, training, evaluating, and improving ML systems that directly shape user outcomes. You’ll partner closely with product, backend, and frontend teams to turn ambiguous problems into measurable model improvements.
What You’ll Do
Help build FINNY’s core models
Design, train, and iterate on custom models that power data imputation, prospect and audience recommendations, campaign customization and personalization, and automations.
Build & improve models in production
Take models from research → experimentation → deployment → iteration
Own offline evaluation, online metrics, and feedback loops
Improve model performance over time through better objectives, features, and training strategies—not just more data
Advanced modeling & experimentation
Apply and adapt techniques such as:
Operate effectively in low-signal, noisy, or cold-start environments
Contribute to ML systems & infrastructure
Work with backend engineers to productionize models reliably and at scale
Help define standards for model versioning, evaluation, deployment, and monitoring
Influence long-term ML strategy and reduce technical debt in modeling workflows
What We’re Looking For
You’re a model builder at heart
You care deeply about how models learn, not just how pipelines run
You’re comfortable reasoning about loss functions, tradeoffs, and evaluation
You enjoy designing solutions when the problem is underspecified and data is imperfect
You’re strong technically
Very strong Python with extensive hands-on experience building ML systems.
Strong statistical and mathematical foundations.
Proven experience training, fine-tuning, and deploying custom models into production, not just experimentation or offline research
Experience designing loss functions, evaluation metrics, and validation strategies aligned with real-world product objectives
Familiarity with model lifecycle management: versioning, reproducibility, monitoring, and iteration in production environments
You’ve shipped ML systems before
You’ve taken models beyond notebooks and into real products
You understand failure modes, monitoring, and iteration in production ML
Startup experience
Your working style
You tackle ambiguity head-on and turn fuzzy problems into concrete experiments
You move fast, iterate, and aren’t precious about first approaches
You communicate clearly about model behavior, limitations, and tradeoffs
In-person, NYC (5 days/week in Chelsea office)
Compensation & Benefits
FINNY offers a competitive compensation package including:
Competitive salary and equity
Medical, dental, and vision insurance
Flexible paid time off
401(k)
Food and meals provided in our NYC office
Team offsites and events
Equal Opportunity Employer
FINNY is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.