Senior Software Engineer, Machine Learning Platform (AI)

Location: San Francisco, CA, USA; onsite role

Salary: $187,000–$259,000 base salary per year, plus bonus, equity, and benefits.

Company

hirify.global is a financial technology company building user-friendly financial products and banking services for millions of members.

What you will do

• Design, build, and operate scalable machine learning and AI infrastructure on AWS.
• Develop platform capabilities for LLM and agentic workloads, including model access, retrieval, tool integration, state management, and workflow orchestration.
• Build evaluation, observability, reliability, governance, privacy, and cost-management systems for models and agents.
• Develop distributed training, batch inference, feature pipelines, streaming, and large-scale processing systems.
• Maintain infrastructure as code, CI/CD workflows, and production platform components.
• Partner with Data Science and ML Engineering teams and participate in on-call rotations.

Requirements

• 5+ years of experience in ML or AI infrastructure, platform engineering, distributed systems, or production ML systems.
• Experience designing distributed systems and large-scale data or compute platforms on AWS using Spark or Ray.
• Working knowledge of LLM application patterns, including retrieval-augmented generation, structured outputs, tool calling, agent orchestration, and evaluation of non-deterministic systems.
• Experience with CI/CD, DevOps, infrastructure as code, containerization, and orchestration with Docker and Kubernetes.
• Strong programming skills in Python, Go, Scala, Java, or similar languages.
• Ability to work onsite in San Francisco, USA.

Nice to have

• Experience shipping LLM-powered or agentic systems to production.
• Experience with model gateways, prompt lifecycle management, retrieval or vector search, tool execution, or agent orchestration frameworks.
• Experience with evaluation, tracing, and observability for non-deterministic AI systems.
• Familiarity with Amazon Bedrock, SageMaker, or equivalent foundation-model platforms.
• GPU workload optimization and CUDA experience.

Culture & Benefits

• In-office policy with four days per week in the office and Fridays from home for employees near an office.
• Bonus eligibility, competitive equity, and comprehensive health, financial, and wellbeing benefits.
• Generous vacation, company-wide paid days off, and an annual wellness stipend.
• Paid parental leave of up to 22 weeks for birthing parents and 12 weeks for non-birthing parents.
• Backup care, commuter benefits, family planning reimbursement, and community support time.