AI-Assisted Coding Engineer Jobs in United States

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.