Summary
✨ AI‑Generated
A well-funded financial technology organization is seeking an AI/ML Engineer who can own both Java backend engineering and applied machine learning. You will build production services, data pipelines, and ML models rather than handing models off for productionization. The role combines Java and Spring Boot with Kafka, Redis, PostgreSQL, and data-warehouse technologies, alongside Python-based ML frameworks. The position follows a hybrid schedule with most weekdays in the office.
Highlights
Own both backend engineering and machine learning in production, build reliable ML services and pipelines, work with real-time data technologies, and develop systems where reliability and explainability are important.
Description
AI/ML Engineer — Java Backend + Applied ML
A well-funded fintech is building the infrastructure that loans and CLO markets have never had.
Trillions of dollars still move through phones, emails, and PDFs.
This team is applying AI, real-time data, and modern software design to a market that's never had it — and needs an engineer who can build production ML systems, not just prototype them.
The role
This is a Java backend engineer who also owns the ML side — you're not handing models off to someone else to productionize, you're building the services, the pipelines, and the models yourself.
You'll take AI solutions from concept through production in a real financial environment where reliability and explainability aren't optional.
NYC-based (Manhattan), 4 days in-office, Friday remote.
What you'll actually build
Production backend services powering AI/ML capabilities — Java, Spring Boot, Kafka, Redis, PostgreSQL, RedshiftML models trained, evaluated, and deployed using Python frameworks (scikit-learn, PyTorch, TensorFlow)Agentic AI systems — multi-agent workflows, tool-use pipelines, orchestration frameworks (MCP or similar)Data pipelines and feature engineering workflows supporting training and inferenceMLOps infrastructure — model versioning, monitoring, A/B testing, automated retrainingWhat we need
2+ years professional software engineering with strong Java and Spring BootExperience with event-driven systems (Kafka), PostgreSQL, Redshift or equivalent data warehousing, RedisSolid grasp of distributed systems, REST API design, microservices2+ years hands-on AI/ML development in Python — real model-building experience, not just API calls to a hosted modelWorking knowledge of ML fundamentals: supervised/unsupervised learning, model evaluation, feature engineering, hyperparameter tuningExperience with scikit-learn, PyTorch, TensorFlow, or XGBoostUnderstanding of LLMs and GenAI — prompt engineering, fine-tuning, RAGBonus: exposure to agentic patterns — tool use, planning, multi-step reasoning, or frameworks like LangChain, LangGraph, CrewAI, Spring AIComp
$130,000–$160,000 base, plus equity and year-end bonus.
Full medical/financial benefits, 90% company-paid healthcare, flexible PTO, daily breakfast/coffee/snacks, onsite gym.
