Junior Machine Learning Engineer, Factset

Python, Docker, and API development, Cloud Architecture, AWS, AI/ML

Salary not provided

AWS

Docker

Python

Heroku

Junior and Mid level

London

Business data & analytics for finance

Be an early applicant

Business data & analytics for finance

1001+ employees

B2BInvestingAnalyticsFinancial Services

Be an early applicant

Salary not provided

AWS

Docker

Python

Heroku

Junior and Mid level

London

1001+ employees

B2BInvestingAnalyticsFinancial Services

Company mission

To provide access to connected financial data, next-gen AI tools, and dedicated support to help clients see more, think bigger, and do their best work.

Job

Company

Role

Who you are

An ideal candidate for the role would be an individual that has experience or a strong interest in working with generative AI and related technologies
They will also have the confidence to meaningfully contribute to team meetings in order to help lead discussions and drive outcomes
2+ years software engineering experience, with a significant portion focused on AI/ML solutions in production environments
Demonstrated expertise in cloud architecture (AWS) and a range of associated services
Working knowledge of Natural Language Processing/Machine Learning/Deep Learning concepts and their applications, with a proven track record of successful model development and deployment
Proficiency in Python, Docker, and API development
Strong technical writing and presentation skills
Familiarity with relational databases and data modeling techniques
Bachelor’s degree in computer science, computer engineering, or relevant

Desirable

Experience with Cloud platforms such as AWS or Heroku
Experience or knowledge of CI/CD concepts and GitHub
An interest in the financial services domain

What the job involves

You will be working on a team in a fast-paced environment where you will have the opportunity to influence the design and architecture of the product
Build new systems to ingest and enrich data into an ontology
Monitor and enhance the accuracy, performance, and observability of our GenAI RAG stack
Evaluate new large language models, tools, and AI engineering techniques
Improve query planning, optimization, and evaluation infrastructure
Partner and collaborate with product development leads to identify technical requirements for future product enhancements
Collaborate with teams across the organization to understand their data

Salary benchmarks

Our take

FactSet is an S&P 500 company creating flexible, open data solutions for investment professionals around the globe. The company was founded at the end of the 1970s, when the prominence of computers spurred the founders to find a way to deliver computer-based financial information. In doing so, FactSet revolutionized the delivery of this data to clients, which had previously been by messenger and on paper.

Investors use FactSet to access instant financial data and analytics that educate their investment decisions. In 2022, FactSet for CRM launched on the Salesforce AppExchange; reaching users looking to get a complete, reliable view of current and prospective customers. As it has grown, the company has continuously responded to changes in the market, and innovated its operations.

As part of the company’s efforts to help clients modernize and improve their market data technology, FactSet partnered with data and analytics company BMLL to offer order book history and analytics in the cloud. The company has also made steps into the cryptocurrency space by collaborating with Coin Metrics, integrating Coin Metrics’ digital assets data into its solutions, whilst embarking on a series of strategic fintech acquisitions over 2023 and 24.

Kirsty

Company Specialist at Welcome to the Jungle

Insights

11% employee growth in 12 months

Glassdoor (4)

Company

Funding (1 round)

May 2003

$0.2m

SEED

Total funding: $0.2m

Company HQ

Norwalk, CT

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