AI Engineer at Jobot
Chicago, IL 60610
About the Job
This Jobot Job is hosted by: Amber Wood
Are you a fit? Easy Apply now by clicking the "Quick Apply" button
and sending us your resume.
Salary: $120,000 - $150,000 per year
A bit about us:
Recognized as a top employer that has had double digit growth for over 50 years.
Why join us?
Job Details
We are seeking a AI Engineer for its Data Science team, 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 such as AWS, Azure, and GCP.
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.
Continuously monitor, evaluate, and enhance the performance and efficiency of ML systems deployed on cloud infrastructures.
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).
Qualifications
At least 4 years of cloud-native experience in machine learning engineering, supporting large infrastructure environments.
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.
Education
Bachelor’s degree in computer science, Engineering, or a related field.
Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.
Are you a fit? Easy Apply now by clicking the "Quick Apply" button
and sending us your resume.
Salary: $120,000 - $150,000 per year
A bit about us:
Recognized as a top employer that has had double digit growth for over 50 years.
Why join us?
- Competitive Compensation
- Full benefits
- Bonus
- Growth Opportunities
- Collaborative culture
Job Details
We are seeking a AI Engineer for its Data Science team, 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 such as AWS, Azure, and GCP.
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.
Continuously monitor, evaluate, and enhance the performance and efficiency of ML systems deployed on cloud infrastructures.
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).
Qualifications
At least 4 years of cloud-native experience in machine learning engineering, supporting large infrastructure environments.
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.
Education
Bachelor’s degree in computer science, Engineering, or a related field.
Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.
Salary
120,000 - 150,000 /year