Senior Machine Learning Engineer (AI)

Location: San Francisco, California, United States; expected to work from the office 3+ days a week. A relocation stipend may be available for relocation to a hirify.global hub in Denver, San Francisco, Nashville, or Santiago.

Base salary or on-target earnings: $207,000–$244,000 USD annually for San Francisco.

Company

hirify.global builds an AI-powered data platform for safe and fair verification and decision-making, including employment and background-check products.

What you will do

• Design, develop, deploy, monitor, and test production ML models and AI services.
• Use LLM APIs such as OpenAI and Anthropic in production systems, selecting between LLMs, fine-tuning, classical models, and rules based on cost, latency, and quality.
• Build clean, tested software with APIs, object-oriented design, error handling, and CI/CD pipelines.
• Partner with Product Engineering, Product, and cross-functional teams to translate business problems into ML solutions and define API contracts.
• Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance.
• Automate pipelines, build agentic workflows, and contribute reusable skills and context to hirify.global’s agentic platform.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent experience.
• 6+ years of professional software development experience, including at least 2 years building production ML systems.
• Strong Python skills and experience writing clean, testable, well-structured code with solid object-oriented design.
• Production experience with LLM APIs, including prompt engineering, structured outputs, function calling, cost management, and evaluation.
• Experience building and maintaining APIs, working with CI/CD pipelines, and shipping software used by other engineers.
• Based in San Francisco or able to relocate to a hirify.global hub; in-office attendance is expected 3+ days per week.

Nice to have

• Experience with MLOps platforms such as MLflow, SageMaker, or Vertex.
• Background in document processing, OCR, or information extraction.
• Experience with PySpark, large-scale data processing, Ruby, dbt, Snowflake, or modern ELT tools.
• Familiarity with compliance-sensitive fintech, legal tech, or HR tech domains.

Culture & Benefits

• Fast-paced, collaborative, impact-focused engineering environment with an emphasis on shipping.
• Learning and development allowance.
• Competitive cash and equity compensation with advancement opportunities.
• 100% medical, dental, and vision coverage.
• Flexible PTO, monthly wellness stipend, and up to $25,000 reimbursement for fertility, adoption, and parental planning services.
• In-office perks include meals, a commuter stipend, snacks, and beverages.