Machine Learning Engineer

Edison Smart®; New York (NY); On-site; USD 216,000 - 264,000; Full time

Benefits offered by this job

Fully covered healthcare

Unlimited PTO

Visa transfers supported

Equity

Job summary

Edison Smart® in New York City is seeking an ML Engineer to translate research into production, collaborating closely with researchers to own training, serving, and the full model lifecycle from experiment to deployment on-site in Manhattan.

You will build pipelines, optimize performance and costs, and contribute to a fast-growing AI/robotics startup backed by solid funding. Competitive compensation includes base up to $240k, equity, healthcare, unlimited PTO, and visa transfers.

Qualifications

• 4+ years in ML engineering or research engineering.
• Hands on PyTorch: trained and debugged models.
• Models taken all the way into production.
• Strong Python with real engineering discipline.
• Cloud, containers and GPU workloads.
• LLM fine tuning, model serving or agent systems.
• Distributed training or inference optimisation.
• Scientific ML or reinforcement learning.

Responsibilities

• Turn research ideas into working, tested code.
• Build and run training and fine tuning pipelines.
• Build the evals that decide if a model is ready to ship.
• Deploy models and improve speed and cost.
• Own how models perform after launch.

Skills

PyTorch

Python

Production ML

Distributed training

LLM fine tuning

Model serving

Tools

Docker

Kubernetes

AWS

GCP

Job description

New York, NY (on-site) | Up to $240k base + equity

I'm working with a well funded AI and robotics startup in NYC. Their robots run real world experiments around the clock, and AI decides what to try next. Small team, serious backing, and models that get used for real.

They need an ML Engineer to take models from research into production, working side by side with their researchers and owning everything from training to serving.

What you'll do

• Turn research ideas into working, tested code
• Build and run training and fine tuning pipelines
• Build the evals that decide if a model is ready to ship
• Deploy models and improve speed and cost
• Own how models perform after launch

What they're looking for

• 4+ years in ML engineering or research engineering
• Hands on PyTorch: you've trained and debugged models yourself
• Models taken all the way into production
• Strong Python with real engineering discipline
• Cloud, containers and GPU workloads
• LLM fine tuning, model serving or agent systems
• Distributed training or inference optimisation
• Scientific ML or reinforcement learning

Package:

Up to $250k base, equity, fully covered healthcare, unlimited PTO. Visa transfers supported.