Lead Machine Learning Engineer

Empower Professionals
New York, United States of America
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 146K

Job location

New York, United States of America

Tech stack

Big Data
Cloud Computing
Github
Python
Machine Learning
Azure
SQL Databases
Systems Architecture
PyTorch
Snowflake
Model Validation
Pandas
Scikit Learn
XGBoost
Machine Learning Operations
Docker

Job description

The Lead Machine Learning Engineer will be responsible for designing and owning the end-to-end machine learning architecture and recommendation engine framework. This role will lead the development of scalable ML solutions, guide technical direction, and drive the transition of models from experimentation to production., Design and implement machine learning system architecture and recommendation engine solutions. Lead model development, deployment, and productionization efforts. Collaborate with data scientists, engineers, and business stakeholders to define technical solutions. Establish ML engineering best practices, model governance, and deployment standards. Provide technical leadership to a small delivery team. Optimize model performance, scalability, and reliability., Python SQL Snowflake Azure Machine Learning GitHub Docker XGBoost/LightGBM/PyTorch

Requirements

Advanced Python development for machine learning (Pandas, Scikit-learn). Experience building and deploying ML models from prototype to production. Strong expertise in SQL and large-scale data processing. Experience with cloud-based ML platforms (Azure Machine Learning preferred). Machine learning model development using XGBoost, LightGBM, or PyTorch., Experience in utilities or other regulated industries. Background in optimization and operations research. Experience leading small technical teams.

In compliance with the salary transparency law, the expected pay range for this role is $70/hr. Actual compensation depends on experience and interview evaluation

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