AI/ML Engineer
- Source: LinkedIn
- LaStellar Group
- $125,000 to $160,000 /yr
- On-site
- New York City
- Full-Time
- Mid level
Job 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, Redshift
- ML 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 inference
- MLOps infrastructure — model versioning, monitoring, A/B testing, automated retraining
What we need
- 2+ years professional software engineering with strong Java and Spring Boot
- Experience with event-driven systems (Kafka), PostgreSQL, Redshift or equivalent data warehousing, Redis
- Solid grasp of distributed systems, REST API design, microservices
- 2+ years hands-on AI/ML development in Python — real model-building experience, not just API calls to a hosted model
- Working knowledge of ML fundamentals: supervised/unsupervised learning, model evaluation, feature engineering, hyperparameter tuning
- Experience with scikit-learn, PyTorch, TensorFlow, or XGBoost
- Understanding of LLMs and GenAI — prompt engineering, fine-tuning, RAG
- Bonus: exposure to agentic patterns — tool use, planning, multi-step reasoning, or frameworks like LangChain, LangGraph, CrewAI, Spring AI
Comp
$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.
Skills
- Java
- spring
- spring-boot
- Kafka
- Redis
- PostgreSQL
- Python
- Scikit-learn
- PyTorch
- Tensorflow
- xgboost
- LangChain
- LangGraph
- crewai
