Machine Learning Engineer

About the role

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.

Responsibilities

• 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, taking them 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.
• Apply and adapt advanced techniques such as operating effectively in low-signal, noisy, or cold-start environments.
• Contribute to ML systems & infrastructure, working with backend engineers to productionize models reliably and at scale.
• Influence long-term ML strategy and reduce technical debt in modeling workflows.

Requirements

• 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 very strong in Python with extensive hands-on experience building ML systems.
• You have strong statistical and mathematical foundations.
• You have proven experience training, fine-tuning, and deploying custom models into production, not just experimentation or offline research.
• You have experience designing loss functions, evaluation metrics, and validation strategies aligned with real-world product objectives.
• You have familiarity with model lifecycle management: versioning, reproducibility, monitoring, and iteration in production environments.
• You’ve shipped ML systems before, understanding failure modes, monitoring, and iteration in production ML.

Qualifications

• You’re strong technically, with a background in machine learning and statistics.
• You have experience working in a startup environment.

Skills

• Python
• Machine Learning

Benefits

• 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

Pay

$180K - $200K

Schedule

Full-time, 5 days/week in Chelsea office, NYC