Job Description
CUNY School of Medicine
Finance Procurement Specialist - Administration and Finance
CUNY School of Medicine • New York, NY, United States • via HERC Jobs
13 hours ago
Full–time
Apply on HERC Jobs
Apply on LinkedIn
Apply directly on ZipRecruiter
Apply directly on JobzMall
Job highlights
Identified by Google from the original job post
Qualifications
Bachelor's degree and four years' related experience required
Applicants must provide a resume and cover letter
Benefits
Non-exempt
COMPENSATION AND BENEFITS
Salary Range: $82,663 - $94,909
5 more items(s)
Responsibilities
Under the direction of the Purchasing & Finance Operations Manager in the Office of Administration and Finance, the Finance Procurement Specialist will execute purchases on behalf of the College from a variety of funding sources in accordance with procurement methods, rules and policies required by the State of New York (STATE), and the City University of New York (CUNY)
In addition to the CUNY Title Overview, the Finance Procurement Specialist duties include but are limited to the following responsibilities:
Collaborate with CUNY MED staff to ensure all activities related to good and services are acquired in accordance with applicable guidelines and regulations and review, recommend and implement process improvements
17 more items(s)
Job description
Finance Procurement Specialist - Administration and Finance
POSITION DETAILS
The CUNY School of Medicine (CUNY SoM) located in the heart of Harlem, New York, is the only medical school in the City University of New York system and the only public medical school in Manhattan. Building upon 50 years of success as the Sophie Davis School of Biomedical Education, the institution transitioned to the ...
Report this listing
DoorDash USA
Engineering Manager, New Business Verticals - Machine Learning
DoorDash USA • New York, NY, United States • via CareersinAudit.com
17 hours ago
Full–time
Apply directly on CareersinAudit.com
Apply on Rise - Jobs
Apply on Jobs For Stevenage Fans
Apply on SaluteMyJob
Apply on KSNT Jobs
Apply on Edinburgh City FC
Apply on KGET Jobs
Apply on JobGet
Job highlights
Identified by Google from the original job post
Qualifications
Lead and grow a team of exceptional machine learning engineers delivering on end-to-end product features with state of the art ML/AI approaches
B.S., M.S., or PhD. in Computer Science or equivalent
7+ years of industry experience
5 more items(s)
Benefits
The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions
Base salary is localized according to an employee's work location
In addition to base salary, the compensation for this role includes opportunities for equity grants
7 more items(s)
Responsibilities
This team also maintains a real-time understanding of in-store item availability employing advanced ML and Computer Vision algorithms
Consumer ML Team: Dedicated to enhancing user engagement and satisfaction through the development of solutions for personalization, discovery, growth, and search
Product Knowledge Graph ML Team: Responsible for creating advanced ML-driven catalog building solutions, significantly utilizing Generative AI to effectively manage and organize product information
7 more items(s)
Job description
Engineering Manager, New Business Verticals - Machine Learning San Francisco, CA; Sunnyvale, CA; Seattle, WA; New York, NY
About the Team DoorDash is seeking an Engineering Manager with an ML/AI background to lead a Machine Learning/Artificial Intelligence team within the New Verticals Machine Learning (NVML) organization.
The NVML organization comprises three core teams:
• Fulfillment, Logistics, and Inventory ML Team: This team focuses on optimizing the matching of orders with capable delivery individuals to ensure high-quality and affordable deliveries using a mix of Operations Research, Deep Learning and classical ML methods. This team also maintains a real-time understanding of in-store item availability employing advanced ML and Computer Vision algorithms.
• Consumer ML Team: Dedicated to enhancing user engagement and satisfaction through the development of solutions for personalization, discovery, growth, and search.
• Product Knowledge Graph ML Team: Responsible for creating advanced ML-driven catalog building solutions, significantly utilizing Generative AI to effectively manage and organize product information.
