Senior ML Engineer

About Smart Asset:

Smart Asset is an online destination for consumer-focused financial information and advice, whose mission is helping people make smart financial decisions, reaching over an estimated 59 million people each month (as of January 2025) through our educational content and personalized calculators and tools. To extend our mission, we also operate Smart Asset Advisor Marketing Platform (AMP), which helps connect consumers with fiduciary financial advisors.

Smart Asset has earned recognition on the Inc. 5000 (#2574 in 2023) and Deloitte Technology Fast 500™ (#250 in 2022) lists. Currently, Smart Asset ranks on Y Combinator’s list of Top 100 Companies. A successful $110 million Series D funding round in 2021 valued the company at over $1 billion.

* Other than application and licensing fees, Smart Asset did not provide compensation for the aforementioned awards.

About the team:

The Machine Learning Engineering team designs, builds, and integrates the core platform that unlocks cutting‑edge capabilities for financial advisors, including features driven by generative AI. Our engineers are relentlessly evolving this platform, empowering groundbreaking applications and features that truly help financial professionals better connect with their clients and grow their businesses.

We are seeking a highly motivated and experienced Machine Learning Engineer to join our growing team. In this role, you will be instrumental in crafting and scaling foundational backend systems across predictive systems and generative AI. You will work across the entire software development lifecycle, from architectural design to deployment and ongoing operations, contributing significantly to our core infrastructure and data strategies, and working hand‑in‑hand with cross‑functional partners like LLM Engineers, Product Owners, and Data Scientists to bring our vision to life.

Responsibilities
:

• Design, develop, and maintain high‑performance, scalable, and secure backend services, primarily using Python and frameworks like FastAPI
• Translate ambiguous business and technical requirements into concrete software designs and actionable tasks for cross‑functional teams
• Work with OLTP databases, including schema design, migration strategies, and performance optimization
• Integrate Smart Asset services with internal and external APIs, including third‑party platforms and existing AWS infrastructure
• Ensure secure ingress and egress of data within our private network environments
• Contribute to the design and implementation of our CI/CD pipelines to ensure continual improvements to our cycle time
• Manage and optimize AWS services, including IAM roles and policies
• Gain a deep understanding of how our Python applications integrate with our Kubernetes (EKS) and future ECS‑based infrastructure
• Operate and maintain production applications at scale, ensuring high availability, performance, and reliability
• Design and implement data collection pipelines specifically for Large Language Models (LLMs)
• Contributed to shared data architecture and data governance practices to ensure the persistence of structured data suitable for analytics and model training
• Explore, integrate, and tune various LLM‑related technologies, such as Retrieval Augmented Generation (RAG) systems, and addressing potential scaling challenges
• Investigate and implement agentic technologies, such as tool calling frameworks (e.g., Auto Gen), to enhance LLM capabilities
• Rapidly prototype user interfaces for internal tools and data exploration, leveraging frameworks like Streamlit, Gradio, or other similar tools that facilitate quick iteration and integration without persistent websockets

Skills/Experience you have
:

• Proven experience as a ML Engineer with a strong focus on Python development
• Experience with cloud platforms, specifically AWS, including IAM, EKS/ECS, and other core services
• Experience operating and scaling a production application
• Experience building integrations with internal and external service providers

Skills/Experience preferred
:

• Experience with LLMs, RAG, embedding vector databases, or agentic technologies.
• Familiarity with product ionizing apps built with…