AI/ML Engineer

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.

• 2+ years professional software engineering with strong Java and Spring Boot \n

• Experience with event-driven systems (Kafka), PostgreSQL, Redshift or equivalent data warehousing, Redis \n

• Solid grasp of distributed systems, REST API design, microservices \n

• 2+ years hands-on AI/ML development in Python - real model-building experience, not just API calls to a hosted model \n

• Working knowledge of ML fundamentals: supervised/unsupervised learning, model evaluation, feature engineering, hyperparameter tuning \n

• Experience with scikit-learn, PyTorch, TensorFlow, or XGBoost

• Production backend services powering AI/ML capabilities - Java, Spring Boot, Kafka, Redis, PostgreSQL, Redshift \n

• ML models trained, evaluated, and deployed using Python frameworks (scikit-learn, PyTorch, TensorFlow) \n

• Agentic AI systems - multi-agent workflows, tool-use pipelines, orchestration frameworks (MCP or similar) \n

• Data pipelines and feature engineering workflows supporting training and inference \n

• MLOps infrastructure - model versioning, monitoring, A/B testing, automated retraining \n

\n, * Understanding of LLMs and GenAI - prompt engineering, fine-tuning, RAG \n

• Bonus: exposure to agentic patterns - tool use, planning, multi-step reasoning, or frameworks like LangChain, LangGraph, CrewAI, Spring AI \n

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Comp

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$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.