At Finster AI, we’re building an AI-native platform for investment research. We were founded in late 2023 by Sid Jayakumar, who had previously spent 7 years at Google DeepMind, and brought together a team with experience across startups and the breadth of financial services and leading AI labs. Our team has worked at places including Google DeepMind, JP Morgan and Meta AI and we’re rapidly expanding while working with early customers. We raised a Pre-Seed in December 2023 from Hoxton Ventures, early backers of Deliveroo and Darktrace and will be announcing our Seed raise shortly.
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We’re building a well-rounded team with multi-disciplinary expertise across product, AI, finance, UI/UX, and engineering to help in our goal of building AI agents that can read, analyse and integrate disparate sources of financial and market data. We’re building for the distinct demands of institutional investors, with accuracy, reliability and privacy at the core of our product.
As an AI Engineer at Finster AI, you will play a key role in designing, building, and integrating AI-driven solutions that power our platform. You’ll work on developing and deploying machine learning models, optimizing performance, and ensuring seamless integration with our microservices-based architecture. This role will give you the opportunity to make a direct impact on the intelligence, reliability, and scalability of our platform, collaborating closely with back-end, data, and product teams to deliver cutting-edge AI solutions.
Key Responsibilities:
- Work on building scalable multi-modal LM based AI agents
- Research and build innovative solutions to Finster relevant AI problems including RAG, semantic search, knowledge representation, tool user, fine-tuning and reasoning in LLMs
- Research and build evaluations, metrics, benchmarks for Finster relevant AI problems
- Present innovative solutions through POCs and demos and convert solutions into high-quality production ready code
- Collaborate with other engineers, product managers, designers and team members to innovate, design and build
You may be a good fit if you:
- Have a degree in Computer Science or relevant fields or relevant experience
- Have strong programming experience and familiarity with Python based deep learning frameworks like Pytorch, JAX, Tensorflow
- Have strong familiarity and knowledge of machine learning concepts
- Have familiarity with ML related maths like linear algebra, probability and statistics, multivariate calculus
- Have strong communication and presentation skills (discussion, brainstorming ideas, technical research writing etc.)
It would be great if you also have:
- Familiarity with recent developments and literature on Large Language Models and AI agents
- Experience in industrial research through industrial research internships or AI/ML engineering roles
- Experience writing production ready code
- Experience in academic research as evidenced through research projects, publications etc.
