Python ML Engineer — Generative AI & Production

Markplace E-services; United States; Remote; USD 110,000 - 165,000; Full time

Benefits offered by this job

Real-world AI projects

Generative AI exposure

Collaborative environment

Career growth opportunities

Competitive salary

Job summary

Markplace E-services is hiring a Python & Machine Learning Developer to design, build, and deploy ML models using Python. You will develop scalable backend apps and REST APIs with FastAPI, and work with Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.

The role involves data preprocessing, feature engineering, model training, and production deployment, plus collaboration with teams to deliver high-performance AI-powered solutions on cloud platforms and databases.

Qualifications

• Hands-on Python, ML, and AI-based app dev.
• Experience with ML libraries and model deployment.
• Strong problem-solving and communication skills.
• Familiar with production monitoring and optimization.

Responsibilities

• Design, develop, and deploy Machine Learning models using Python.
• Build scalable backend applications and REST APIs using FastAPI.
• Work with Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.
• Perform data preprocessing, feature engineering, model training, and evaluation.
• Develop and integrate AI/ML solutions into production applications.
• Work with SQL databases, cloud platforms, and model deployment.
• Collaborate with development teams to build scalable, high-performance solutions.

Skills

Python

Machine Learning

OOP

SQL

Communication

Tools

FastAPI

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

AWS

Docker

ML Ops

LangChain

LLMs

RAG

Job description

Markplace E-services is hiring a Python & Machine Learning Developer to design, build, and deploy ML models using Python. You will develop scalable backend apps and REST APIs with FastAPI, and work with Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch.

The role involves data preprocessing, feature engineering, model training, and production deployment, plus collaboration with teams to deliver high-performance AI-powered solutions on cloud platforms and databases.