Job description 

You might be a good fit if you

• Seize the opportunity to explore gen AI, machine learning and its real-world applications at scale. Jump in!
• Rapidly prototype ideas, approaches and methods in the AI space.
• Read, implement and improve the latest papers in the AI field
• A relentless passion to learn more and go deep into machine learning and generative AI concepts, bringing your research to engineer products that shape Citi’s future.
• Be a game-changer, ready to step beyond your designated role
• Bring your deep-dive software engineering expertise
• Thrive in a results-driven environment, where flexibility fuels impact
• Love the synergy of pair programming? So do we!

What you’ll do within the Tech Strategy team:

• Lead the research and conceptual builds of Generative AI products,
• Design and build high-quality, highly reliable products with user experience at the centre
• Be responsible for turning research insight into best-in-class AI platforms for the bank
• Creating firsts in the Generative AI space for Citi as part of the team that defines the strategic direction for the bank
• Continually iterate and scale Generative AI products, whilst continually researching the advancements in technology and listening to the needs of the customers (internal)
• Mentor and nurture other engineers to help them grow their skills and expertise

Experience that will help you succeed in this role

• A well-known contributor to opensource and always thinking out of the box tooling, using and standardizing with methods of creating APIs , ML/Ops automation and more.
• Have experience supporting fast-paced startup engineering teams
• Understanding of language models and transformers
• Have used LangChain and even contributed to the project.
• Fluency in at least two programming language, with preference for Python, JavaScript/Typescript, Golang
• Experience designing control and sandboxing systems for AI research
• Pytorch or TensorFlow experience
• Experience maintaining and/or contributing to bug bounty and responsible disclosure programs
• Rich understanding of vector stores and search algorithms
• Large-scale ETL development
• Direct engineering experience of high performance, large-scale ML systems
• Deep hands on knowledge of Kubernetes, developing backend platforms and engineering APIs that scale
• Hands on MLOps experience, with an appreciation of the end-to-end CI/CD process

What we believe in

• We do not have boundaries between engineering and research, and we expect all our technical staff to contribute to both as needed.
• We take a product-focused approach and care about building solutions that are robust, scalable, and easy to use.
• We enjoy working in a fast-paced team tackling cutting-edge problems by constantly testing and learning.
• We enjoy pair programming for our products, we are lean in our approach and remove bureaucracy where we see it.
• We believe in delivering fast, iterating and pivot as we go, rather than defining the perfect solution upfront.