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Applied Artificial Intelligence Jobs (NOW HIRING)

Applied AI ML Director

Seattle, WA · On-site

$180 - $320/hr

Are you passionate about harnessing the power of artificial intelligence and machine learning to ... As an Applied AI ML Director in the Commercial & Investment Bank at JPMorganChase, you'll play a ...

New

Applied AI ML Director

Seattle, WA · On-site

$223K - $325K/yr

Are you passionate about harnessing the power of artificial intelligence and machine learning to ... As an Applied AI ML Director in the Commercial & Investment Bank at JPMorganChase, you'll play a ...

Are you passionate about harnessing the power of artificial intelligence and machine learning to ... As an Applied AI ML Director in the Commercial & Investment Bank at JPMorganChase, you'll play a ...

New

Are you passionate about harnessing the power of artificial intelligence and machine learning to ... As an Applied AI ML Director in the Commercial & Investment Bank at JPMorganChase, you'll play a ...

New

Are you passionate about harnessing the power of artificial intelligence and machine learning to ... As an Applied AI ML Director in the Commercial & Investment Bank at JPMorganChase, you'll play a ...

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Applied Artificial Intelligence information

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$11K

$102.9K

$133K

How much do applied artificial intelligence jobs pay per year?

As of Aug 17, 2026, the average yearly pay for applied artificial intelligence in the United States is $102,938.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $132,500.00 per year, depending on experience, location, and employer.

What is an applied artificial intelligence?

An Applied Artificial Intelligence job focuses on developing and implementing AI solutions to solve real-world problems. Professionals in this field apply machine learning, deep learning, and data-driven algorithms to improve decision-making, automation, and efficiency in various industries. They work closely with data scientists, engineers, and domain experts to integrate AI into existing systems or create new intelligent applications. This role requires strong programming skills, knowledge of AI frameworks, and an understanding of business or industry-specific challenges.

What are the common responsibilities and collaborative aspects of an applied artificial intelligence?

In an Applied Artificial Intelligence role, you will typically be involved in developing, testing, and deploying AI models to solve real-world business problems. Your daily tasks may include data preprocessing, model training, evaluation, and working closely with cross-functional teams such as data engineers, product managers, and domain experts. Collaboration is a significant part of this position, as your insights often inform product development, process automation, and decision-making across the organization. This role offers exposure to cutting-edge technologies and provides opportunities to see the direct impact of your work in various industry applications.

What are the key skills and qualifications needed to thrive in applied artificial intelligence, and why are they important?

To thrive in Applied Artificial Intelligence, a solid background in computer science, mathematics, and statistics—typically supported by a relevant degree—is essential. Experience with machine learning frameworks such as TensorFlow or PyTorch, programming languages like Python, and industry certifications in AI or data science are highly valued. Strong problem-solving skills, effective communication, and the ability to work collaboratively make candidates stand out. These competencies are vital for designing, implementing, and deploying AI solutions that address complex real-world challenges across diverse industries.

How to get a job in applied artificial intelligence?

To get a job in applied artificial intelligence, develop strong skills in programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and data analysis. Obtain relevant education, such as a degree in computer science or data science, and build a portfolio of projects or experience in AI applications to demonstrate your expertise.

Is an applied artificial intelligence degree worth it?

An applied artificial intelligence degree provides foundational knowledge in machine learning, data analysis, and programming, which are essential skills for AI roles. It can improve job prospects and earning potential, especially when combined with practical experience and proficiency in tools like Python and TensorFlow.
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What cities are hiring for Applied Artificial Intelligence jobs?

Cities with the most Applied Artificial Intelligence job openings:

What states have the most Applied Artificial Intelligence jobs?

States with the most job openings for Applied Artificial Intelligence jobs include:

Infographic showing various Applied Artificial Intelligence job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $102,938 per year, or $49.5 per hour.

Applied AI ML Director

JPMorgan Chase & Co.

Seattle, WA • On-site

$180 - $320/hr

Other

This job post has expired today. Applications are no longer accepted.


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

71st of 171 rated banks


Job description

Are you passionate about harnessing the power of artificial intelligence and machine learning to solve real-world challenges? At JPMorganChase, we’re transforming the way payments work in the Commercial & Investment Bank by leveraging classical and cutting-edge AI/ML technologies.

As an Applied AI ML Director in the Commercial & Investment Bank at JPMorganChase, you’ll play a pivotal role in strategizing and building innovative solutions that enhance trust, safety, and operational efficiency for one of the world’s leading financial institutions. You will own solutions end-to-end, from problem framing and data strategy to production deployment and measurement. You will remain hands-on while setting technical direction and partnering across product, engineering, data, risk, and compliance stakeholders.

Job Responsibilities
  • Demonstrated expertise in several areas from Graph Networks, Neural Networks, NLP, Vision, Classical ML and other technologies
  • Domain expertise to develop and improve Trust & Safety problems in payment processing (e.g. Fraud Prevention, Authorization Optimization, Abuse).
  • Own end-to-end delivery of problems in Payments (Trust & Safety or otherwise) solutions, from opportunity sizing and requirements through production rollout and iteration.
  • Demonstrated ability to envision and develop AI/ML strategy that has platform wide impact within payments Organization.
  • Define evaluation strategies and success metrics, including offline validation, error analysis, robustness testing, and controlled online measurement where appropriate.
  • Establish model lifecycle practices including reproducibility, testing, monitoring, drift detection, and incident response to sustain reliable production performance.
  • Partner with risk and compliance stakeholders to ensure appropriate documentation, controls, explainability expectations, and audit-ready processes.
  • Drive technical decisions through design reviews, code and model reviews, and pragmatic standards that raise quality and delivery velocity.
  • Communicate tradeoffs and recommendations to senior stakeholders, translating model behavior into decision-ready business impact.
Required Qualifications, Capabilities, and Skills
  • PhD in applied artificial intelligence, machine learning concepts or similar with 5+ years of experience or MS in applied artificial intelligence, machine learning concepts or similar with 8+ years experince.

  • Experience building and delivering applied machine learning or natural language processing solutions with measurable outcomes in production.

  • Strong programming skills in Python and experience using modern machine learning frameworks such as PyTorch or TensorFlow.

  • Hands-on experience with document extraction and natural language processing techniques including text classification and information extraction.

  • Experience designing data-driven solutions using SQL and distributed processing tools such as Spark or equivalent.

  • Experience deploying and operating machine learning services or pipelines in a cloud environment such as Amazon Web Services (or equivalent).

  • Demonstrated ability to translate ambiguous business problems into structured machine learning plans, including data strategy, evaluation, rollout, and operationalization.

  • Strong communication and collaboration skills, including the ability to explain technical tradeoffs to technical and non-technical partners.

Preferred Qualifications, Capabilities, and Skills
  • Experience with optical character recognition and document understanding workflows for scanned or semi-structured documents.

  • Experience with modern natural language processing architectures such as transformer-based models and techniques for optimization and efficient inference.

  • Experience with machine learning operations practices and tooling, including model registries, continuous integration and delivery for machine learning, and observability.

  • Experience with real-time or event-driven architectures supporting low-latency inference and feature generation.

  • Experience applying document extraction or natural language processing in payments, financial services, or regulated environments.

FEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.

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