Member of Technical Staff - AI/ML - Autonomous Finance AI Platform
Andiamo, San Francisco, CA, United States
Member of Technical Staff — AI/ML Engineering (Financial Technology)
Build intelligent systems that redefine how businesses manage financial operations. A rapidly growing financial technology platform is modernizing accounts receivable processes for B2B organizations, replacing manual, time‑intensive workflows with intelligent automation. Supporting industries such as manufacturing, chemicals, and industrial operations, this platform enables finance teams to operate with greater speed, accuracy, and insight.
This role offers the opportunity to apply cutting‑edge artificial intelligence techniques to real‑world business challenges—developing systems that directly impact how companies manage invoices, payments, and financial data at scale.
Role Overview
As a Member of Technical Staff specializing in AI/ML, you will design and deliver production‑grade machine learning systems that power core financial workflows. You will take advanced AI concepts—including large language models and retrieval‑based systems—and transform them into scalable, reliable applications used by enterprise customers. This is a highly hands‑on engineering role for someone who enjoys building end‑to‑end AI systems and seeing them drive measurable business outcomes. You will work closely with cross‑functional teams to bring intelligent automation into everyday financial processes.
Key Responsibilities
AI Application Development
Design, build, and deploy machine learning solutions that address complex financial operations challenges, including invoice processing, payment matching, and document analysis.
Feature Innovation & Optimization
Develop and enhance AI‑driven features that improve efficiency and accuracy in financial workflows. Continuously refine models and systems based on performance metrics and real‑world usage.
Model Adaptation & Fine‑Tuning
Apply and optimize modern AI architectures such as large language models and retrieval‑augmented systems to meet domain‑specific requirements in finance.
Scalable AI Infrastructure
Build robust, production‑ready pipelines that support data ingestion, model training, inference, and monitoring while ensuring high availability and performance.
Workflow Automation
Design intelligent automation solutions that reduce manual effort in accounts receivable and related financial processes.
Cross‑Functional Collaboration
Partner with product managers, engineers, and customers to understand business needs and translate them into effective technical solutions.
Performance Measurement
Establish evaluation frameworks to track model accuracy, system performance, and business impact. Continuously improve solutions based on data and feedback.
Required Qualifications
Software Engineering Experience
At least five years of experience in software development, including experience building and deploying production systems.
AI/ML Expertise
Minimum of two years of hands‑on experience working with applied machine learning in production environments.
Large Language Models
Experience integrating and fine‑tuning LLMs for real‑world applications.
Retrieval‑Based Systems
Experience building and deploying retrieval‑augmented generation (RAG) systems or similar architectures for data‑intensive workflows.
Machine Learning Frameworks
Proficiency in Python and experience with frameworks such as PyTorch, TensorFlow, or transformer‑based models.
MLOps Practices
Understanding of model deployment, monitoring, experimentation, and continuous improvement practices, including A/B testing.
Data Engineering Skills
Strong experience with data preprocessing, feature engineering, and preparing datasets for machine learning applications.
System Integration
Experience integrating AI solutions into enterprise platforms or SaaS environments.
Problem‑Solving Ability
Ability to translate complex business requirements into scalable, effective technical solutions.
What Makes a Strong Candidate
Experience delivering AI solutions that solve real business problems—not just experimental prototypes.
Ability to balance innovation with practicality, ensuring systems are both cutting‑edge and reliable.
Comfort working in fast‑paced environments where priorities evolve quickly.
Strong collaboration skills with the ability to work across technical and non‑technical teams.
A mindset focused on continuous improvement, experimentation, and measurable impact.
Compensation & Benefits
This role offers a competitive compensation package, including a strong base salary and equity participation. Full‑time employees may receive comprehensive benefits such as medical, dental, and vision coverage, retirement savings options with employer matching, flexible paid time off, and parental leave.
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Build intelligent systems that redefine how businesses manage financial operations. A rapidly growing financial technology platform is modernizing accounts receivable processes for B2B organizations, replacing manual, time‑intensive workflows with intelligent automation. Supporting industries such as manufacturing, chemicals, and industrial operations, this platform enables finance teams to operate with greater speed, accuracy, and insight.
This role offers the opportunity to apply cutting‑edge artificial intelligence techniques to real‑world business challenges—developing systems that directly impact how companies manage invoices, payments, and financial data at scale.
Role Overview
As a Member of Technical Staff specializing in AI/ML, you will design and deliver production‑grade machine learning systems that power core financial workflows. You will take advanced AI concepts—including large language models and retrieval‑based systems—and transform them into scalable, reliable applications used by enterprise customers. This is a highly hands‑on engineering role for someone who enjoys building end‑to‑end AI systems and seeing them drive measurable business outcomes. You will work closely with cross‑functional teams to bring intelligent automation into everyday financial processes.
Key Responsibilities
AI Application Development
Design, build, and deploy machine learning solutions that address complex financial operations challenges, including invoice processing, payment matching, and document analysis.
Feature Innovation & Optimization
Develop and enhance AI‑driven features that improve efficiency and accuracy in financial workflows. Continuously refine models and systems based on performance metrics and real‑world usage.
Model Adaptation & Fine‑Tuning
Apply and optimize modern AI architectures such as large language models and retrieval‑augmented systems to meet domain‑specific requirements in finance.
Scalable AI Infrastructure
Build robust, production‑ready pipelines that support data ingestion, model training, inference, and monitoring while ensuring high availability and performance.
Workflow Automation
Design intelligent automation solutions that reduce manual effort in accounts receivable and related financial processes.
Cross‑Functional Collaboration
Partner with product managers, engineers, and customers to understand business needs and translate them into effective technical solutions.
Performance Measurement
Establish evaluation frameworks to track model accuracy, system performance, and business impact. Continuously improve solutions based on data and feedback.
Required Qualifications
Software Engineering Experience
At least five years of experience in software development, including experience building and deploying production systems.
AI/ML Expertise
Minimum of two years of hands‑on experience working with applied machine learning in production environments.
Large Language Models
Experience integrating and fine‑tuning LLMs for real‑world applications.
Retrieval‑Based Systems
Experience building and deploying retrieval‑augmented generation (RAG) systems or similar architectures for data‑intensive workflows.
Machine Learning Frameworks
Proficiency in Python and experience with frameworks such as PyTorch, TensorFlow, or transformer‑based models.
MLOps Practices
Understanding of model deployment, monitoring, experimentation, and continuous improvement practices, including A/B testing.
Data Engineering Skills
Strong experience with data preprocessing, feature engineering, and preparing datasets for machine learning applications.
System Integration
Experience integrating AI solutions into enterprise platforms or SaaS environments.
Problem‑Solving Ability
Ability to translate complex business requirements into scalable, effective technical solutions.
What Makes a Strong Candidate
Experience delivering AI solutions that solve real business problems—not just experimental prototypes.
Ability to balance innovation with practicality, ensuring systems are both cutting‑edge and reliable.
Comfort working in fast‑paced environments where priorities evolve quickly.
Strong collaboration skills with the ability to work across technical and non‑technical teams.
A mindset focused on continuous improvement, experimentation, and measurable impact.
Compensation & Benefits
This role offers a competitive compensation package, including a strong base salary and equity participation. Full‑time employees may receive comprehensive benefits such as medical, dental, and vision coverage, retirement savings options with employer matching, flexible paid time off, and parental leave.
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