At a Glance
- Tasks: Design and implement AI/ML applications to solve complex business problems.
- Company: Join J.P. Morgan, a global leader in financial services with a commitment to diversity.
- Benefits: Enjoy a collaborative work environment with opportunities for professional growth and development.
- Why this job: Be part of innovative projects that make a real impact using cutting-edge technology.
- Qualifications: Experience in Python, machine learning, and data analysis is essential.
- Other info: Flexible working arrangements and a focus on inclusion make this a great place to thrive.
The predicted salary is between 43200 - 72000 £ per year.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As an AI/ML Python Engineer at JPMorgan Chase within the Client Onboarding and KYC Engineering team, your responsibilities will include probing intricate business problems and employing sophisticated algorithms to design, evaluate, and implement AI/ML applications or models to resolve these issues. You will be required to leverage the company's extensive data assets from both internal and external sources using tools like Python, Spark, and AWS. Additionally, your role will encompass extracting business insights from technical results and effectively communicating them to a non-technical audience.
Job Responsibilities
- Design and architect end to end solutions in AI domain, from Pattern matching, Chatbot implementation, and using GenAI.
- Proactively develop an understanding of key business problems and processes.
- Execute tasks throughout the model development process, including data wrangling/analysis, model training, testing, and selection.
- Generate structured and meaningful insights from data analysis and modelling exercises and present them in an appropriate format according to the audience.
- Collaborate with other data scientists and machine learning engineers to deploy machine learning solutions.
- Conduct ad-hoc and periodic analysis as required by business stakeholders, the model risk function, and other groups.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and advanced applied experience.
- Experience in statistical inference and experimental design (such as probability, linear algebra, calculus).
- Data wrangling: understanding complex datasets, cleaning, reshaping, and joining messy datasets using Python.
- Practical expertise and work experience with ML projects, both supervised and unsupervised.
- Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R.
- Understanding and usage of the OpenAI API.
- NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets.
- Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG).
- Experience in anomaly detection techniques, algorithms, and applications.
- Excellent problem-solving, communication (verbal and written), and teamwork skills.
Preferred qualifications, capabilities, and skills
- Experience with big data frameworks, with a preference for Databricks.
- Experience with databases, including SQL (Oracle, Aurora), and Vector DB.
- Familiarity with version control systems such as Bitbucket and GitHub.
- Experience with graph analytics and neural networks.
- Experience working with engineering teams to operationalize machine learning models.
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
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
AI/ML Python Software Engineer III employer: J.P. MORGAN-1
Contact Detail:
J.P. MORGAN-1 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Python Software Engineer III
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning, especially those relevant to financial services. This will not only help you understand the business problems better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the AI/ML field, particularly those working at JPMorgan Chase or similar companies. Attend industry meetups or webinars to build connections and gain insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss your previous projects in detail, focusing on your problem-solving approach and the impact of your work. Be ready to explain complex concepts in simple terms, as you'll need to communicate technical results to non-technical stakeholders.
✨Tip Number 4
Brush up on your Python skills, particularly with libraries like NumPy, pandas, and scikit-learn. Consider working on a small project that showcases your ability to handle data wrangling and model development, as practical experience can set you apart from other candidates.
We think you need these skills to ace AI/ML Python Software Engineer III
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly read the job description for the AI/ML Python Software Engineer III position. Understand the key responsibilities and required skills, such as experience with Python, machine learning projects, and data wrangling.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job requirements. Emphasise your proficiency in Python, machine learning frameworks, and any experience with big data tools or NLP techniques.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI/ML and your problem-solving abilities. Mention specific projects or experiences that demonstrate your expertise in the areas mentioned in the job description.
Highlight Communication Skills: Since the role involves communicating technical results to a non-technical audience, ensure you provide examples of how you've effectively communicated complex information in previous roles or projects.
How to prepare for a job interview at J.P. MORGAN-1
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant libraries like NumPy, pandas, and scikit-learn. Highlight specific projects where you've applied machine learning techniques, especially in AI/ML contexts.
✨Understand the Business Context
Demonstrate your ability to connect technical solutions to business problems. Research JPMorgan Chase's operations and think about how your skills can help solve their specific challenges in client onboarding and KYC.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. Since you'll need to present insights to non-technical audiences, focus on how you can make your findings accessible and actionable.
✨Collaborative Mindset
Emphasise your teamwork skills and experiences. Be ready to discuss how you've collaborated with data scientists and engineers in the past to deploy machine learning solutions successfully.