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Job Description
As a AI / ML Engineer play an important role in advancing our primary AI platform.
Expectations:
- Lead projects focused on integrating and optimizing large language models (LLMs), embedding models, and semantic retrieval systems within our products.
- Design, build, and deploy sophisticated multimodal retrieval and agentic systems that deliver powerful insights from unstructured and structured financial data sources.
- Drive the next generation of agentic capabilities within our platform, with a focus on composability, advanced function calling, and modular AI orchestration techniques.
- Continuously refine our retrieval methodologies and AI outputs by actively leveraging customer feedback, ensuring high accuracy and relevance.
- Explore innovative approaches and rapidly prototype new AI-driven features, directly impacting our client’s workflows.
- Collaborate closely with engineering, product, and customer-facing teams, communicating ideas clearly and effectively to achieve business outcomes.
Desired Qualifications
- 2+ years of experience deploying machine learning models in production.
- Demonstrated experience integrating closed-source LLM APIs and fine-tuning open-source models
- Proven expertise with embedding models and semantic retrieval systems such as Pinecone, Weaviate, FAISS, Chroma, PGVector, etc.
- Experience developing multimodal retrieval solutions that integrate diverse data types, including textual, numerical, and structured data.
- Strong Python proficiency, including practical knowledge of frameworks like Hugging Face, PyTorch, TensorFlow, or LangChain.
- Passion for staying current with cutting-edge AI research, tools, and industry trends.
- Ability to thrive in ambiguous environments, independently scoping and executing projects end-to-end.
- Excellent communication skills, fostering effective collaboration across technical and business teams.
Additional Qualifications
- Prior experience building or optimizing AI agentic systems leveraging function-calling, orchestration frameworks, and modular architectures.
- Deep familiarity with financial data retrieval challenges and techniques
- Demonstrated experience in performance tuning, scalability improvements, and reliability engineering for AI-driven retrieval systems.
- Entrepreneurial mindset or previous experience working in a high-growth startup environment.
- Knowledge of or interest in free-form generative AI capabilities and their application within complex business scenarios.
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