Applied AI ML - Senior Associate - Machine Learning Engineer

J.P. Morgan; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

An established industry player is seeking an Applied AI / ML Senior Associate Machine Learning Engineer to join a high-performing team dedicated to driving innovation in financial services. This role combines cutting-edge AI techniques with unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance state-of-the-art AI applications while collaborating with talented professionals. As a key contributor, you will build robust data science capabilities and communicate insights effectively to diverse audiences. If you're passionate about AI and eager to make a significant impact, this is the perfect opportunity for you.

Qualifications

• Hands-on experience in an ML engineering role is essential.
• PhD in a quantitative discipline is required.
• Experience with MLOps tooling for model management.

Responsibilities

• Build scalable Data Science capabilities for business use cases.
• Collaborate with engineering teams to deploy ML services.
• Research and analyze datasets using statistical techniques.

Skills

Machine Learning Engineering

Natural Language Processing (NLP)

Computer Vision

Statistical Analysis

MLOps

Data Communication

Education

PhD in Computer Science

PhD in Mathematics

PhD in Statistics

Tools

PyTorch

NumPy

Pandas

Ray

Kubeflow

Spark

Hadoop

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

• Build robust Data Science capabilities which can be scaled across multiple business use cases
• Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems
• Research and analyse data sets using a variety of statistical and machine learning techniques
• Communicate AI capabilities and results to both technical and non-technical audiences
• Document approaches taken, techniques used and processes followed to comply with industry regulation
• Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions.
• 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

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

Preferred qualifications, capabilities, and skills

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