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Recommender Systems Jobs Near Me

JPMorganChase

Applied AI ML-Vice President

Columbus, OH · On-site

Classification, Regression, or Recommender Systems). Company : With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial ...

J.P. Morgan

Applied AI ML-Vice President

Columbus, OH · On-site

Classification, Regression, or Recommender Systems). ABOUT US Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial ...

Battelle

Network Systems Administrator

Columbus, OH · On-site

$81K - $116K/yr

Conducts periodic classified system reviews and self-inspections, identifies compliance gaps or operational risks, recommends corrective actions, and coordinates with ISSMs, FSOs, ISSOs, system ...

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As of Aug 13, 2026, the average yearly pay for recommender systems in the United States is $111,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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Applied AI ML-Vice President

JPMorganChase

Columbus, OH • On-site

Full-time

Re-posted 27 days ago

Job description

Job Summary:
JPMorganChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. In this role, you will apply strong technical judgment to enhance machine learning solutions and drive innovation, ensuring that the technology products are secure, scalable, and reliable.
Responsibilities:
• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Drive innovation in machine learning solutions, ensuring scalability, flexibility, and future-proof architecture
• Act as a thought leader and trusted advisor to executive leadership, providing strategic recommendations on machine learning initiatives and solutions
• Architect and oversee the development of next-generation machine learning models and systems leveraging cutting-edge technologies
• Ensure the platform supports complex use cases, including real-time predictions, big data processing, and advanced analytics
• Promote software and model quality, integrity, and security across the organization
Qualifications:
Required:
• BS in Computer science or similar fields with 5+ years experience or MS in Computer science or similar fields with 3+ years experience, with training and work experience in LLM/NLP and search.
• Proven track record of building and scaling software and or machine learning platforms in high-growth or enterprise environments
• Experience in machine learning frameworks, ML Ops tools and practices.
• Strong proficiency in engineering programming languages (e.g., Python, Java) and infrastructure as code (e.g., Terraform, CloudFormation)
• Proficient in building AI Agents (e.g., LangChain, LangGraph, AutoGen), integration of tools (e.g., API) and RAG based solutions (e.g., open search)
• Hands-on experience with software development pipeline and orchestration tools (e.g., Jenkins, GitLab CI/CD)
Preferred:
• Optional, great to have - experience in developing large-scale machine learning solutions based on big data to solve real world problems (e.g. Classification, Regression, or Recommender Systems).
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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