Applied AI ML - Senior Associate - Machine Learning Engineer

JPMorgan Chase; London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Join a leading financial services firm as an Applied AI / ML Senior Associate Machine Learning Engineer. You will leverage cutting-edge AI techniques and unique data assets to optimize business decisions and automate processes, working on innovative AI-powered products in a collaborative environment.

Qualifications

• Hands on experience in an ML engineering role.
• Track record of developing, deploying business critical machine learning models.
• Specialism in NLP or Computer Vision.

Responsibilities

• Build robust Data Science capabilities across multiple business use cases.
• Collaborate with software engineering team to deploy Machine Learning services.
• Research and analyse data sets using statistical and machine learning techniques.

Skills

Machine Learning

Natural Language Processing

Computer Vision

Statistical Analysis

Communication

Education

PhD in a quantitative discipline

Tools

PyTorch

NumPy

Pandas

Job description

Join a high performing team of applied AI experts to drive innovation and new capabilities in the Commercial & Investment Bank.

As an Applied AI / ML Senior Associate Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state-of-the-art in AI as applied to financial services, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical machine learning. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI-powered products and services and increasing opportunity for re-use of foundational components through careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets.

Job responsibilities

1. Build robust Data Science capabilities which can be scaled across multiple business use cases
2. Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems
3. Research and analyse data sets using a variety of statistical and machine learning techniques
4. Communicate AI capabilities and results to both technical and non-technical audiences
5. Document approaches taken, techniques used and processes followed to comply with industry regulation
6. Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions
7. Act as an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate's experience

Required qualifications, capabilities, and skills

1. Hands on experience in an ML engineering role
2. PhD in a quantitative discipline, e.g., Computer Science, Mathematics, Statistics
3. Track record of developing, deploying business critical machine learning models
4. Broad knowledge of MLOps tooling - for versioning, reproducibility, observability etc.
5. Experience monitoring, maintaining, enhancing existing models over an extended time period
6. Specialism in NLP or Computer Vision
7. Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders, etc.)
8. Extensive experience with pytorch, numpy, pandas
9. Knowledge of open source datasets and benchmarks in NLP / Computer Vision
10. Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.)
11. Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders

Preferred qualifications, capabilities, and skills

1. Experience designing/ implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray)
2. Experience of big data technologies (e.g., Spark, Hadoop)
3. Have constructed batch and streaming microservices exposed as REST/gRPC endpoints
4. Familiarity with GraphQL

About us

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals, and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

About the Team

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services, and payments. Corporations, governments, and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk, and extends liquidity in markets around the world.