AI/ML Engineer

LaStellar Group; New York (NY); Hybrid; USD 130,000 - 160,000; Full time

Benefits offered by this job

Equity

Year-end bonus

Medical benefits

Company-paid healthcare

Onsite gym

Breakfast & snacks

Flexible PTO

Job summary

LaStellar Group in New York City is seeking a backend engineer who also owns the ML side, building production ML systems in a fintech environment. You’ll deliver services, pipelines, and models end-to-end, ensuring reliability and explainability.

You will ship production-grade Java/Spring Boot backends that power AI/ML capabilities, train and deploy models with Python, and design data pipelines for training and inference.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Java

Spring Boot

Kafka

PostgreSQL

Redis

REST APIs

Microservices

Python ML

ML frameworks

LLMs GenAI

Tools

scikit-learn

PyTorch

TensorFlow

XGBoost

LangChain

Job description

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

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.