AI/ML Engineer

QTech US, Inc
Philadelphia, 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

Job location

Remote
Philadelphia, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Continuous Integration
Data Cleansing
Graph Database
Python
Machine Learning
Natural Language Processing
TensorFlow
Azure
Software Engineering
SQL Databases
Enterprise Software Applications
PyTorch
Large Language Models
Snowflake
Spark
Model Validation
Generative AI
GIT
AI Platforms
PySpark
Scikit Learn
Kubernetes
Information Technology
Deployment Automation
HuggingFace
Machine Learning Operations
Docker
Databricks

Job description

We are seeking an experienced Senior AI/ML Engineer to design, develop, and deploy enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will possess strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), LangChain, Vector Databases, and cloud AI services on AWS or Azure. This role involves building scalable machine learning pipelines, deploying production-grade AI models, optimizing model performance, and collaborating with cross-functional teams to deliver innovative AI-driven solutions., Design, develop, and deploy AI/ML models for enterprise applications. Build scalable machine learning pipelines and data preprocessing workflows. Develop and optimize LLM, NLP, and Generative AI solutions. Integrate AI models with cloud platforms and production systems. Monitor model performance, retrain models, and improve model accuracy. Build scalable inference pipelines and support production AI deployments. Collaborate with Data Engineers, Data Scientists, and Software Development teams. Participate in model evaluation, testing, documentation, and continuous improvement initiatives. Follow MLOps best practices for model deployment, monitoring, and lifecycle management. Required Skills: Python TensorFlow PyTorch Scikit-learn Large Language Models (LLMs) Generative AI Retrieval-Augmented Generation (RAG) LangChain Vector Databases AWS AI/ML Services or Azure AI/ML Services SQL Data Engineering Fundamentals Docker Kubernetes Git CI/CD Machine Learning Pipelines Data Preprocessing Model Deployment NLP

Requirements

Experience with MLflow or Kubeflow. Experience with Apache Spark or PySpark. Experience using Hugging Face Transformers. Experience with Databricks and Snowflake. Knowledge of Knowledge Graphs and Graph Databases. Experience implementing enterprise MLOps solutions. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Best Regards

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