ML Engineer: Production-Scale AI & Personalization

FINNY; New York (NY); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Competitive salary and equity

Medical, dental, and vision insurance

Flexible paid time off

Food and meals provided in our NYC办公室

Job summary

FINNY, a growth platform for financial advisors based in Chelsea, NYC, is seeking a machine learning engineer who will own and improve core models powering search, matching, and recommendations.

You’ll design, train, and deploy ML systems end-to-end, collaborate with product, backend, and frontend teams, and help set standards for model versioning, evaluation, and monitoring in production. In-person in NYC.

Qualifications

• 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.

Responsibilities

• Design, train, and iterate on custom models powering search, matching, and recommendations.
• Operate offline evaluation, online metrics, and feedback loops.
• Improve model performance through better objectives, features, and training strategies.
• Collaborate with backend engineers to productionize models reliably at scale.
• Define standards for model versioning, evaluation, deployment, and monitoring.
• Influence long-term ML strategy and reduce technical debt in modeling workflows.

Skills

Python (ML systems)

Statistical foundations

Training and deployment

Model lifecycle management

Startup experience

Job description

FINNY, a growth platform for financial advisors based in Chelsea, NYC, is seeking a machine learning engineer who will own and improve core models powering search, matching, and recommendations.

You’ll design, train, and deploy ML systems end-to-end, collaborate with product, backend, and frontend teams, and help set standards for model versioning, evaluation, and monitoring in production. In-person in NYC.