Match score not available

Machine Learning Engineer

72% Flex
Remote: 
Full Remote
Contract: 
Work from: 
Illinois (USA)

Offer summary

Qualifications:

Cloud-native experience with machine learning engineering and AI platforms in a large-scale environment., Experience using major cloud services (Azure, AWS, GCP) for deploying ML models..

Key responsabilities:

  • Design and implement ML pipelines integrated within cloud architectures.
  • Operationalize ML models on cloud AI platforms and optimize data architectures to enhance performance.
  • Lead integration of ML models into system architectures in a cloud environment.
  • Collaborate with cloud advisors to leverage advanced features and establish best practices around AI Operations.
  • Continuously monitor and enhance performance and efficiency of ML systems on cloud infrastructures.
Brilliant® logo
Brilliant® Human Resources, Staffing & Recruiting SME https://www.brilliantfs.com/
51 - 200 Employees
See more Brilliant® offers

Job description

Logo Jobgether

Your missions

Summary: This Machine Learning Engineer is responsible for developing and deploying AI solutions within core business functions using cloud-native technologies. This role involves ensuring scalability, availability, and efficiency of AI deployments, and establishing best practices in AI operations. Candidates should have cloud-native experience with machine learning engineering and AI platforms in a large-scale environment. Experience operationalizing GenAI applications is not required, but will be an advantage.

Responsibilities

  • Design and implement end-to-end machine learning pipelines that are fully integrated within cloud-native architectures, ensuring scalability and robustness.
  • Work closely with data scientists to operationalize machine learning models on cloud AI platforms, transitioning from experimental prototypes to production-grade solutions.
  • Optimize data architectures to enhance the performance and scalability of ML systems on cloud platforms: Azure
  • Lead the integration of ML models into existing and new system architectures, focusing on compatibility and high performance in a cloud environment. This includes designing and implementing robust APIs.
  • Collaborate with cloud architecture advisors to leverage advanced features of cloud technologies and AI platforms
  • Establish and evangelize best practices around AI Operations (including MLOps and LLMOps).
  • Continuously monitor, evaluate, and enhance the performance and efficiency of ML systems deployed on cloud infrastructures.

Skills

  • Demonstrated experience with AI platforms on the cloud, such as Azure Machine Learning, Google AI Platform, or AWS SageMaker.
  • Strong proficiency in using major cloud services (Azure, AWS, GCP) for deploying ML models and managing data pipelines.
  • Proficient in Python, SQL, and cloud-native technologies such as Kubernetes and Docker.
  • Experience using Linux OS
  • Strong problem-solving skills, organizational abilities, and effective communication skills.
  • Experience operationalizing GenAI applications or assistants.

#Tech2023

Required profile

Experience

Industry :
Human Resources, Staffing & Recruiting
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Soft Skills

  • Problem Solving
  • Strong Communication
  • Organizational Skills

Go Premium: Access the World's Largest Selection of Remote Jobs!

  • Largest Inventory: Dive into the world's largest remote job inventory. More than half of these opportunities can't be found on standard platforms.
  • Personalized Matches: Our AI-driven algorithms ensure you find job listings perfectly matched to your skills and preferences.
  • Application fast-lane: Discover positions where you rank in the TOP 5% of applicants, and get personally introduced to recruiters with Jobgether.
  • Try out our Premium Benefits with a 7-Day FREE TRIAL.
    No obligations. Cancel anytime.
Upgrade to Premium

Find more Machine Learning Engineer jobs