Software Engineer II - Performance Engineering

Reposted 2 Days Ago
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La Blanche, Manche, Normandie
In-Office
Junior
Aerospace • Big Data • Fintech • Software • Analytics
The Role
As a Software Engineer II, you will enhance AI capabilities, manage the software lifecycle, write clean code, and promote teamwork in a financial solutions environment.
Summary Generated by Built In

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.  

At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients’ needs and exceeding their expectations.  

Your Team’s Impact 

Portfolio Vault serves Asset Managers and Asset Owners as a centralised solution for storing, locking, and reporting portfolio returns and analytics. Designed to be a single source of truth, it ensures consistent and reliable data across the organisation. 

By joining our team of skilled Java Engineers, you’ll become part of an Agile, collaborative environment that fosters growth and innovation. You’ll also have the unique opportunity to work alongside an active Machine Learning community, gaining hands-on mentorship and development support. 

As a Machine Learning Engineer, your goal will be to thoughtfully integrate LLMs and other AI techniques into our products and internal processes. Rather than introducing LLMs by default, you will aim to apply them where they add real value, enhancing existing capabilities, enabling new use cases or improving team productivity. 

This position is based in Paris, allowing you to work alongside established machine learning teams and benefit from collaborative synergies in this location. 

Technical stack: Java JDK 21,Vue.JS, Kubernetes, FactSet.io, AWS, Redis, MCP, Agentic workflows, RAG, SQL.

 

What You’ll Do 

Prompt Engineering 

- Design effective prompts to maximise AI utility 

- Develop prompt guidelines and best practices for the team 

- Design and optimise AI prompts

- Develop prompt guidelines and best practices

- Leverage MCP tooling for prompt management and experimentation

- Architect and deploy agentic workflows

- Test and evaluate prompt effectiveness in complex scenarios

- Share knowledge and train team members in prompt engineering

- Collaborate with cross-functional teams on AI-driven solutions

  

Technical Excellence 

- In collaboration with agentic tooling (Claude Code, Cursor, Copilot), help your team to manage the entire software development lifecycle, from theinitialdesign and coding to testing and the deployment of applications 

- Deploy and support ML-driven agentic solutions 

- Write and deliver clean, thoroughly tested code that is reliable, maintainable, and scalable 

 

Cross-Functional Collaboration 

- Work closely with engineering and product teams to ensure adherence to best practices 

- Foster clear communication and teamwork to efficiently execute complex projects 

 

Leadership 

- Coach a team of experienced engineers, helping them to improve their productivity 

- Bring your experience, promoting a culture of innovation and continuous learning within the team 

 

What We’re Looking For 

- 1-2 Years experience with AI/ML and Python  

- Master's degree in Computer Science or equivalent training 

- Ability to articulate and quickly adopt development best practices 

- Ability to build strong relationships and work with engineering peers to solve problems and overcome obstacles 

- Familiarity with ML, NLP and GenAI (including RAG, Prompt Engineering, Vector DBs) 

- Experience with Agentic workflows and MCP 

- Familiarity with deep learning libraries (Keras, PyTorch, Tensorflow 

- Experience with Docker and AWS services is preferred 

- Work experience on ML Ops is preferred 

- Work experience with Jupyter Notebooks is preferred 

- Familiarity with deep learning libraries (Keras, PyTorch, Tensorflow)  is a bonus

- Experience in software development in Java is preferred  

- Familiarity with version control systems (Git) is preferred 

- Database and SQL general knowledge (Postgres/SQL) is a bonus 

Company Overview: 

FactSet (NYSE:FDS | NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn. 

At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law. 

Top Skills

AWS
Java Jdk 21
Keras
Kubernetes
PyTorch
Redis
SQL
TensorFlow
Vue
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The Company
HQ: Norwalk, CT
10,310 Employees
Year Founded: 1978

What We Do

FactSet creates flexible, open data and software solutions for tens of thousands of investment professionals around the world, providing instant access to financial data and analytics that investors use to make crucial decisions.

For 40 years, through market changes and technological progress, our focus has always been to provide exceptional client service. From more than 60 offices in 23 countries, we’re all working together toward the goal of creating value for our clients, and we’re proud that 95% of asset managers who use FactSet continue to use FactSet, year after year.

As big as we grow, as far as we reach, and as successful as we become, we stay connected to our clients and to each other.

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