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Senior AI/ML Engineer
QTech US IncPhiladelphia, PA🇺🇸United StatesPosted 17 Jul 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
Job Title: Senior AI/ML Engineer
Location: Philadelphia, PA | Wilmington, DE | Columbus, OH | Chicago, IL | Minneapolis, MN | Detroit, MI | St. Louis, MO
Duration: 12+ Months Contract
Employment Type: W2 Only (No C2C)
Location: Philadelphia, PA | Wilmington, DE | Columbus, OH | Chicago, IL | Minneapolis, MN | Detroit, MI | St. Louis, MO
Duration: 12+ Months Contract
Employment Type: W2 Only (No C2C)
Job Summary:
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.
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.
Key Responsibilities:
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.
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
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
Preferred Qualifications:
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.
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:
Sophia Sinclair
Phone:
Email:
Sophia Sinclair
Phone:
Email:
Skills
Docker
SQL
AWS
MLOps
MLflow
Machine Learning
NLP
Scikit-learn
Snowflake
Apache
Apache Spark
Azure
Databricks
Generative AI
Git
Hugging Face
Kubernetes
LLM
PyTorch
Python
TensorFlow
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