Sr. Machine Learning Engineer

Testing Site - JPMC; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Testing Site - JPMC is seeking a Senior Machine Learning Engineer to advance our products using large-scale data and ML techniques. You will develop scalable features, manage ML Ops, and tackle ranking and relevance challenges across multiple lines of business.

The role emphasizes building production-ready ML solutions, mentoring peers, and collaborating with stakeholders to drive impact across platforms.

Qualifications

• Master's degree or PhD with relevant experience in ML/AI fields.
• Strong knowledge of ML algorithms, data structures, and software engineering practices.
• Experience with large-scale data processing and ML model deployment.

Responsibilities

• Oversee analysis of complex datasets to inform decisions on real-world applications.
• Lead development and implementation of models and algorithms to enhance systems and products.
• Supervise data analysis activities and ensure effective visualizations are provided.
• Ensure writing and deployment of production-grade software.
• Identify risks in ML solutions and strategize mitigations.
• Communicate complex ML topics clearly to senior management and stakeholders.
• Foster cross-functional collaboration to uphold standards.

Skills

Machine learning

Graph learning

Recommendation systems

Network analysis

Natural language processing

Reinforcement learning

MLOps

Gen AI

LLMs

Education

Master's degree in Computer Science / Machine Learning

PhD in Computer Science / Machine Learning

Tools

AWS

GCP

Azure

Job description

The mission of the Digital Intelligence team is to leverage large-scale computation, substantial datasets, and machine learning to enhance our most crucial customer products across a broad spectrum. We manage a wide array of impactful products and services, reaching countless customers and households. We place high value on our customers' direct feedback and employ a truly agile methodology to incorporate improvements that enhance user experiences.

As a Sr. Machine Learning Engineer in the Digital Intelligence team, you will leverage large-scale computation, substantial datasets, and machine learning to enhance our most crucial customer products across a broad spectrum. Your expertise will promote the team to solve complex relevance and ranking problems, develop scalable features, and manage ML Ops for building innovative systems that benefit our customers across all lines of business.

Job Responsibilities:

• Oversee the analysis of complex datasets to inform decisions on real-world applications.
• Lead the development and implementation of models and algorithms to enhance existing systems, processes, and products.
• Supervise data analysis activities and ensure effective visualizations are provided.
• Ensure the writing and deployment of software code in production systems is efficient and meets standards.
• Anticipate risks associated with machine learning solutions and prediction/classification systems and strategize mitigation.
• Communicate complex issues clearly and credibly to senior management and stakeholders.
• Foster a transparent cross-functional work environment and influence peers and team members to uphold these standards.

Required qualifications, capabilities and skills:

• Master's degree in computer Science, Machine Learning or related field with 5-7 years of relevant experience Ph.D in computer Science, Machine Learning, or a related field with 3 year of experience.
• Expertise in one or more of the following areas: machine learning, Graph learning, recommendation systems, network analysis, natural language processing, Reinforcement learning, MLOps, Gen AI, LLMs.
• Solidunderstandingofcore CS concepts, including common data structures and algorithms.

Preferred qualifications, capabilities and skills:

• Experienced in conducting design and code reviews.
• Proficient in cloud environments such as AWS, GCP, or Azure.
• Experienced in managing and deriving insights from large, both unstructured and structured datasets.