Recruiting From Scratch
Member of Technical Staff - Product Machine Learning
Recruiting From Scratch, San Francisco, California, United States, 94199
Role Title: Member of Technical Staff – Product Machine Learning
Location: San Francisco, CA (Onsite, 5 days/week – Union Square) Company Stage of Funding: Acquired by a Public Company (Post-Series Startup Environment) Office Type: Onsite, 5 days/week Salary: $200K–$325K base + bonus + equity Company Description
Our client is a fast-growing AI startup recently acquired by a leading global technology company. They’ve retained their startup agility and innovative culture while gaining the resources and stability of an established enterprise. The team is building next-generation machine learning systems that transform how financial professionals process and analyze complex data. Their core platform leverages cutting-edge AI to automate and structure large volumes of unstructured financial documents—delivering accuracy, scalability, and time savings for clients across accounting, asset management, and financial services. What You Will Do
Build and enhance ML and product infrastructure that powers AI-driven document processing systems.
Design and iterate on datasets, inference systems, and evaluation pipelines to continuously improve performance and accuracy.
Work directly with end users (financial professionals, accountants) to understand workflows and integrate feedback into the product roadmap.
Collaborate cross-functionally with engineers, designers, and product leads to ship high-quality ML-powered features at scale.
Develop expert systems that encode domain knowledge into scalable software systems.
Contribute to an engineering culture that values rapid iteration, product impact, and measurable results.
Ideal Candidate Background
5+ years of experience building and deploying ML systems in production environments.
Proven experience integrating ML models into end-user products (enterprise or consumer).
Strong foundation in Python and modern ML tooling (e.g., PyTorch, TensorFlow, or JAX).
Experience working with large datasets, data quality optimization, and evaluation metrics.
Excellent communication skills and comfort working directly with customers or stakeholders.
Demonstrated history of ownership and impact in a fast-paced startup or product-focused environment.
Preferred Qualifications
Experience with LLMs, LLM APIs, or large-scale inference pipelines.
Familiarity with financial data or document-heavy domains.
Previous experience at high-velocity AI or data infrastructure companies.
Track record of technical leadership or mentorship within a small, high-performing team.
Compensation, Benefits, and Other Details
Base Salary: $200K–$325K
Equity & Bonus: Competitive package including stock options and performance bonuses
Benefits: Comprehensive health, dental, and vision coverage; 401(k); and generous PTO
Work Environment: Onsite in Union Square, San Francisco — collaborative and hands-on
Visa Support: Sponsorship available for qualified candidates
Team Culture: Small, tight-knit, and product-driven team focused on high ownership and rapid iteration
Why This Role is Exciting:
This is an opportunity to join a technically elite team at the intersection of AI, data infrastructure, and financial automation. You’ll work on challenging ML problems with tangible real-world impact—backed by enterprise resources but guided by startup speed and ambition.
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Location: San Francisco, CA (Onsite, 5 days/week – Union Square) Company Stage of Funding: Acquired by a Public Company (Post-Series Startup Environment) Office Type: Onsite, 5 days/week Salary: $200K–$325K base + bonus + equity Company Description
Our client is a fast-growing AI startup recently acquired by a leading global technology company. They’ve retained their startup agility and innovative culture while gaining the resources and stability of an established enterprise. The team is building next-generation machine learning systems that transform how financial professionals process and analyze complex data. Their core platform leverages cutting-edge AI to automate and structure large volumes of unstructured financial documents—delivering accuracy, scalability, and time savings for clients across accounting, asset management, and financial services. What You Will Do
Build and enhance ML and product infrastructure that powers AI-driven document processing systems.
Design and iterate on datasets, inference systems, and evaluation pipelines to continuously improve performance and accuracy.
Work directly with end users (financial professionals, accountants) to understand workflows and integrate feedback into the product roadmap.
Collaborate cross-functionally with engineers, designers, and product leads to ship high-quality ML-powered features at scale.
Develop expert systems that encode domain knowledge into scalable software systems.
Contribute to an engineering culture that values rapid iteration, product impact, and measurable results.
Ideal Candidate Background
5+ years of experience building and deploying ML systems in production environments.
Proven experience integrating ML models into end-user products (enterprise or consumer).
Strong foundation in Python and modern ML tooling (e.g., PyTorch, TensorFlow, or JAX).
Experience working with large datasets, data quality optimization, and evaluation metrics.
Excellent communication skills and comfort working directly with customers or stakeholders.
Demonstrated history of ownership and impact in a fast-paced startup or product-focused environment.
Preferred Qualifications
Experience with LLMs, LLM APIs, or large-scale inference pipelines.
Familiarity with financial data or document-heavy domains.
Previous experience at high-velocity AI or data infrastructure companies.
Track record of technical leadership or mentorship within a small, high-performing team.
Compensation, Benefits, and Other Details
Base Salary: $200K–$325K
Equity & Bonus: Competitive package including stock options and performance bonuses
Benefits: Comprehensive health, dental, and vision coverage; 401(k); and generous PTO
Work Environment: Onsite in Union Square, San Francisco — collaborative and hands-on
Visa Support: Sponsorship available for qualified candidates
Team Culture: Small, tight-knit, and product-driven team focused on high ownership and rapid iteration
Why This Role is Exciting:
This is an opportunity to join a technically elite team at the intersection of AI, data infrastructure, and financial automation. You’ll work on challenging ML problems with tangible real-world impact—backed by enterprise resources but guided by startup speed and ambition.
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