AI/ML Engineer

TechniPros, LLC
Philadelphia, PA, United States
25 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Cloud Engineering Python (Programming Language) Machine Learning Tensorflow Standard Sql IBM Watson Health Pytorch Large Language Models Prompt Engineering Generative AI
+3 more
AI Platforms Kubernetes Machine Learning Operations

Job description

  • We are hiring experienced AI/ML Engineers to support a cutting-edge Healthcare AI initiative. The ideal candidate will possess extensive experience in Machine Learning, Generative AI, MLOps, and cloud-native AI platforms with expertise in AWS., * Design, develop, and deploy AI/ML solutions on AWS.
  • Build scalable Machine Learning pipelines.
  • Develop Generative AI applications using LLMs and RAG architectures.
  • Implement Prompt Engineering techniques for enterprise AI applications.
  • Develop and deploy models using SageMaker and Bedrock.
  • Build MLOps pipelines using MLflow and Kubeflow.
  • Work with vector databases for semantic search applications.
  • Collaborate with healthcare stakeholders to build Clinical NLP solutions

Requirements

  • Python
  • SQL
  • AWS
  • Machine Learning
  • MLOps
  • LLMs
  • Generative AI
  • Retrieval Augmented Generation (RAG)
  • Prompt Engineering
  • PyTorch
  • TensorFlow
  • scikit-learn
  • SageMaker
  • Bedrock
  • MLflow
  • Kubeflow
  • Vector Databases

Mandatory Skills:

  • Python
  • AWS
  • Machine Learning
  • MLOps
  • LLM
  • GenAI
  • RAG
  • Prompt Engineering
  • SageMaker
  • Bedrock
  • MLflow
  • Kubeflow
  • Vector Databases

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · WWC 2023

1:39 min

Fundamentals of tensors and the TensorFlow library

Håkan Silfvernagel · LIVE

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · WWC 2022

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

3:53 min

Architecting machine learning projects with the PAI platform

Qiyang Duan · LIVE

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · WWC Europe 2026

Videos

See all

Related articles

See all