AI/ML Engineer

Propertyvalue Quantum Technologies Llc
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 181K

Job location

Remote

Tech stack

Artificial Intelligence
Google BigQuery
Cloud Engineering
Computer Programming
Continuous Integration
Information Engineering
Data Flow Control
Python
Machine Learning
TensorFlow
Azure
Google Cloud Platform
Enterprise Software Applications
PyTorch
Large Language Models
Generative AI
AI Platforms
Scikit Learn
Kubernetes
Machine Learning Operations
Virtual Agents
REST
Software Version Control
Data Pipelines
Automation Anywhere
Docker
Microservices

Job description

  • Design and develop AI/ML and Agentic AI solutions for automation and intelligent decision-making.
  • Build, deploy, and maintain end-to-end machine learning pipelines.
  • Implement AI/ML solutions using Google Cloud Platform services including Vertex AI, BigQuery ML, and Dataflow.
  • Develop agent-based and multi-step AI workflows integrated with enterprise applications.
  • Build scalable batch and real-time data pipelines.
  • Monitor, optimize, and maintain AI models in production environments.
  • Collaborate with architects and engineering teams on AI platform design.
  • Implement MLOps practices including CI/CD, model versioning, governance, and monitoring.

Requirements

  • 5 10 years of experience in AI/ML, Data Engineering, or Cloud Engineering.

  • Strong programming expertise in Python.

  • Hands-on experience with ML frameworks:

  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Strong experience with Google Cloud AI/ML services:
  • Vertex AI
  • BigQuery ML
  • Dataflow
  • Experience with Generative AI, LLMs, and Agentic AI (multi-step reasoning, orchestration, AI agents).
  • Experience building and deploying ML pipelines in production.
  • Knowledge of Microservices and REST API integration.
  • Hands-on experience with Docker, Kubernetes, and CI/CD.
  • Experience building real-time and batch data pipelines.
  • Strong understanding of MLOps, including model governance, monitoring, and version control.

Apply for this position