Job description
At Aris Investing, we’re building next-gen financial intelligence systems driven by real-time insights,
thematic data, and secure, scalable architecture. As an AI/ML Associate Engineer, you will play a key
role in prototyping and deploying AI-driven solutions, particularly around LLM-based applications and
modern ML infrastructure.
This is a hands-on, R&D-heavy role—perfect for an AI enthusiast eager to explore the intersection of
large language models, financial data, and real-world applications.
Assist in building context-aware LLM applications using LangChain, LlamaIndex, and vector
databases.
Implement and evaluate retrieval-augmented generation (RAG) systems tailored to internal
knowledge (JSONs, tabular data, metadata).
Run R&D experiments on embedding models, fine-tuning strategies, and open-source LLMs
(Mistral, LLaMA 3, etc.).
Contribute to MLOps pipelines for managing and deploying ML models (versioning, monitoring, API
endpoints).
Design and test prompt engineering strategies, tool-based agents, and multi-modal extensions.
Collaborate with backend, data, and platform teams to integrate AI solutions into production systems
(AWS, Lambda, Glue, Iceberg).
Document findings, build reusable modules, and maintain AI playground notebooks and dashboards.
Proficiency in Python and basic experience with LangChain, HuggingFace Transformers, or
LlamaIndex.
Familiarity with foundational models (GPT, Claude, Mistral, etc.) and prompt engineering.
Understanding of RAG workflows and semantic search.
Basic understanding of ML model life cycles and evaluation.
Good communication skills and strong curiosity.
Experience with AWS tools (S3, Lambda, Glue) or vector DBs (Weaviate, FAISS, Pinecone).
Exposure to orchestration tools (Airflow, Dagster) or CI/CD pipelines.
Background in finance, knowledge graphs, or structured JSON data parsing.
How to apply
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