Applied AI Engineer at Blend

United States

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

FinTech, BankingIndustries

Requirements

5+ years of progressive professional experience as an Applied AI Engineer, Machine Learning Engineer, or a similar role, with a proven track record of architecting and deploying complex AI solutions in production, particularly involving large language models, other foundational models, and agentic systems
Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related quantitative field
Expert proficiency in Python and extensive experience with relevant libraries for data processing, API development, and advanced interaction with foundational models (e.g., Hugging Face Transformers, OpenAI API, Anthropic API, Google AI SDKs)
Deep understanding and hands-on experience with the practical application, fine-tuning, and deployment of large foundational models in real-world scenarios
Expert-level experience with designing and implementing sophisticated AI agents and multi-agent systems using at least one major agentic framework (e.g., DSPy, LangChain, LlamaIndex, AutoGen)

Responsibilities

Collaborate with cross-functional teams to understand and translate business requirements into technical specifications & code
Architect, design, and lead the implementation of complex AI/ML solutions, with a strong focus on leveraging and orchestrating large foundational models (e.g., GPT, Llama, Gemini, Claude, Stable Diffusion) and pre-trained AI services from cloud providers or open-source libraries
Take a leading role in designing, implementing, and deploying sophisticated AI agents and multi-agent systems using frameworks like DSPy, LangChain, LlamaIndex, AutoGen, or similar, to automate complex tasks, enable advanced reasoning, and drive new product capabilities
Define and build robust, scalable APIs and services that expose advanced AI functionalities, including those powered by foundational models and agentic systems, serving as core components for other engineering teams and product features
Develop, evangelize, and refine advanced prompt engineering strategies and techniques to maximize the performance, safety, and desired outputs from foundational models across diverse applications
Design and optimize robust data pipelines for efficient AI model consumption, with a particular emphasis on architecting and implementing highly performant and scalable Retrieval Augmented Generation (RAG) patterns for foundational models
Develop a rigorous eval framework to assess model performance and track model drift, data quality issues, and performance degradation
Identify and troubleshoot defects and issues, ensuring timely resolution
Participate in the team’s on-call rotation
Participate in code reviews to maintain code quality and ensure best practices
Encourage great habits to enhance team practices by participating in code reviews & offering peer mentorship and guidance
Propose new ideas and build features end-to-end

Skills

GPT

Llama

Gemini

Claude

Stable Diffusion

DSPy

LangChain

LlamaIndex

AutoGen

Prompt Engineering

AI Agents

Multi-Agent Systems

APIs

Blend

Streamlines lending process for financial institutions

About Blend

Blend simplifies the lending process for financial institutions with its digital platform, allowing them to process over $3 billion in loans daily. The platform includes automated verifications, instant pre-approvals, and seamless electronic closings, which enhance efficiency and reduce costs. Blend stands out from competitors with its modular architecture and no-code configuration tools, enabling quick adaptation to market changes and personalized customer experiences. The company's goal is to improve loan processing efficiency and customer acquisition for its clients.

San Francisco, CaliforniaHeadquarters

2012Year Founded

$646.9MTotal Funding

IPOCompany Stage

Fintech, Financial ServicesIndustries

501-1,000Employees

Benefits

Meaningful equity and a 401(k) plan

Comprehensive health benefits

Wellness benefits covering a variety of wellness activities, gym memberships, fitness classes and more

16 weeks of paid parental leave

Generous vacation policy

Work from home office set up stipend and internet stipend during COVID-19

Risks

Increased competition from emerging fintechs could erode Blend's market share.

Recent stock price decline may indicate investor concerns about Blend's future.

Volatility in the FinTech IPO Index suggests potential market instability for Blend.

Differentiation

Blend's platform processes over $4 billion in loans daily, showcasing its scalability.

The company offers a modular architecture, allowing quick adaptation to market changes.

Blend's partnerships with major banks enhance its credibility and market reach.

Upsides

Growing demand for digital lending boosts Blend's market potential.

Partnerships with fintechs like Astra enhance Blend's service offerings.

Automated workflows reduce costs and improve efficiency for financial institutions.

Land your dream remote job 3x faster with AI

Try Jobo Free