Upstart
Staff Applied Machine Learning Engineer, LLM Applications
Upstart, Myrtle Point, Oregon, United States, 97458
About Upstart
Upstart is the leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than 80% of borrowers are approved instantly, with zero documentation to upload.
Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.
Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!
The Team Upstart’s new
Applied LLM team
is building foundational infrastructure that democratizes access to generative AI for every product and engineering team across the company. This is a cross‑functional team at the intersection of machine learning, product, and engineering. Our mission is to bring the power of ML—particularly large language models (LLMs) and generative AI—to life in Upstart’s core products.
Staff Applied Machine Learning Engineer As a
Staff Applied Machine Learning Engineer
focused on building
LLM applications , you'll work closely with researchers, product managers, platform engineers, and designers to ship intelligent features that elevate the user experience and expand the capabilities of our systems.
Position Location This role is available in the following locations: San Mateo, Columbus, Austin, Remote.
Time Zone Requirements This team operates on the East/West Coast time zones.
Travel Requirements This team has regular on‑site collaboration sessions. These occur 3–4 days per quarter at one of our offices. If you need to travel to make these meetups, Upstart will cover all travel related expenses.
How you’ll make an impact:
Design and build user‑facing ML features that harness LLMs and generative AI to unlock new product capabilities
Partner with product, design, and ML research to prototype and deliver high‑impact, ML‑powered experiences
Own the technical architecture and implementation strategy for applied ML systems—balancing latency, observability, and iteration speed
Build scalable services and APIs that bring model outputs to users in trustworthy and intuitive ways
Collaborate across platform, infra, and legal/compliance teams to ensure ML deployments meet standards for safety, fairness, and performance
Establish and evangelize best practices for prompt design, model evaluation, and experimentation across the org
What we’re looking for:
Minimum qualifications:
6+ years of software engineering experience, with 2+ years working directly on ML‑driven products or intelligent systems
Proven ability to lead complex initiatives across engineering, product, and research stakeholders
Strong backend development skills (e.g., Python with FastAPI or Flask), plus experience with cloud‑native tooling (e.g., Kubernetes, Docker, Terraform)
Experience integrating LLMs or ML models into production systems, including APIs and user‑facing applications
Excellent communication skills and a collaborative, product‑minded approach
Ability to think rigorously about system design, latency tradeoffs, and user impact when working with ML features
Preferred qualifications:
Experience shipping GenAI or LLM‑powered features using frameworks like LangChain, LlamaIndex, or OpenAI APIs
Familiarity with retrieval‑augmented generation (RAG), vector search (e.g., FAISS, Pinecone), and real‑time inference patterns
Proficiency in full‑stack development, including front‑end work with React or similar frameworks
Strong intuition for prompt engineering, model testing, and evaluation methodologies
Experience navigating complex requirements around explainability, user trust, or compliance in ML applications
Track record of influencing architecture or product direction at a team or org level
What you’ll love:
Competitive Compensation (base + bonus & equity)
Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart
401(k) with 100% company match up to $4,500 and immediate vesting and after‑tax savings
Employee Stock Purchase Plan (ESPP)
Life and disability insurance
Generous holiday, vacation, sick and safety leave
Supportive parental, family care, and military leave programs
Annual wellness, technology & ergonomic reimbursement programs
Social activities including team events and onsites, all‑company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering
Catered lunches + snacks & drinks when working in offices
United States | Remote - Anticipated Base Salary Range $178,400 — $246,800 USD
At Upstart, your base pay is one part of your total compensation package. The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location— with our “digital first” philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job‑related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
In addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).
Upstart is a proud Equal Opportunity Employer. We are dedicated to ensuring that underrepresented classes receive better access to affordable credit, and are just as committed to embracing diversity and inclusion in our hiring practices. We celebrate all cultures, backgrounds, perspectives, and experiences, and know that we can only become better together.
If you require reasonable accommodation in completing an application, interviewing, completing any pre‑employment testing, or otherwise participating in the employee selection process, please email candidate_accommodations@upstart.com
https://www.upstart.com/candidate_privacy_policy
#J-18808-Ljbffr
Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.
Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!
The Team Upstart’s new
Applied LLM team
is building foundational infrastructure that democratizes access to generative AI for every product and engineering team across the company. This is a cross‑functional team at the intersection of machine learning, product, and engineering. Our mission is to bring the power of ML—particularly large language models (LLMs) and generative AI—to life in Upstart’s core products.
Staff Applied Machine Learning Engineer As a
Staff Applied Machine Learning Engineer
focused on building
LLM applications , you'll work closely with researchers, product managers, platform engineers, and designers to ship intelligent features that elevate the user experience and expand the capabilities of our systems.
Position Location This role is available in the following locations: San Mateo, Columbus, Austin, Remote.
Time Zone Requirements This team operates on the East/West Coast time zones.
Travel Requirements This team has regular on‑site collaboration sessions. These occur 3–4 days per quarter at one of our offices. If you need to travel to make these meetups, Upstart will cover all travel related expenses.
How you’ll make an impact:
Design and build user‑facing ML features that harness LLMs and generative AI to unlock new product capabilities
Partner with product, design, and ML research to prototype and deliver high‑impact, ML‑powered experiences
Own the technical architecture and implementation strategy for applied ML systems—balancing latency, observability, and iteration speed
Build scalable services and APIs that bring model outputs to users in trustworthy and intuitive ways
Collaborate across platform, infra, and legal/compliance teams to ensure ML deployments meet standards for safety, fairness, and performance
Establish and evangelize best practices for prompt design, model evaluation, and experimentation across the org
What we’re looking for:
Minimum qualifications:
6+ years of software engineering experience, with 2+ years working directly on ML‑driven products or intelligent systems
Proven ability to lead complex initiatives across engineering, product, and research stakeholders
Strong backend development skills (e.g., Python with FastAPI or Flask), plus experience with cloud‑native tooling (e.g., Kubernetes, Docker, Terraform)
Experience integrating LLMs or ML models into production systems, including APIs and user‑facing applications
Excellent communication skills and a collaborative, product‑minded approach
Ability to think rigorously about system design, latency tradeoffs, and user impact when working with ML features
Preferred qualifications:
Experience shipping GenAI or LLM‑powered features using frameworks like LangChain, LlamaIndex, or OpenAI APIs
Familiarity with retrieval‑augmented generation (RAG), vector search (e.g., FAISS, Pinecone), and real‑time inference patterns
Proficiency in full‑stack development, including front‑end work with React or similar frameworks
Strong intuition for prompt engineering, model testing, and evaluation methodologies
Experience navigating complex requirements around explainability, user trust, or compliance in ML applications
Track record of influencing architecture or product direction at a team or org level
What you’ll love:
Competitive Compensation (base + bonus & equity)
Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart
401(k) with 100% company match up to $4,500 and immediate vesting and after‑tax savings
Employee Stock Purchase Plan (ESPP)
Life and disability insurance
Generous holiday, vacation, sick and safety leave
Supportive parental, family care, and military leave programs
Annual wellness, technology & ergonomic reimbursement programs
Social activities including team events and onsites, all‑company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering
Catered lunches + snacks & drinks when working in offices
United States | Remote - Anticipated Base Salary Range $178,400 — $246,800 USD
At Upstart, your base pay is one part of your total compensation package. The anticipated base salary for this position is expected to be within the below range. Your actual base pay will depend on your geographic location— with our “digital first” philosophy, Upstart uses compensation regions that vary depending on location. Individual pay is also determined by job‑related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
In addition, Upstart provides employees with target bonuses, equity compensation, and generous benefits packages (including medical, dental, vision, and 401k).
Upstart is a proud Equal Opportunity Employer. We are dedicated to ensuring that underrepresented classes receive better access to affordable credit, and are just as committed to embracing diversity and inclusion in our hiring practices. We celebrate all cultures, backgrounds, perspectives, and experiences, and know that we can only become better together.
If you require reasonable accommodation in completing an application, interviewing, completing any pre‑employment testing, or otherwise participating in the employee selection process, please email candidate_accommodations@upstart.com
https://www.upstart.com/candidate_privacy_policy
#J-18808-Ljbffr