Senior Platform Engineer, Machine Learning

About Us:

We are establishing a new state of trust for global commerce and capital markets through automating and streamlining the work of assurance and audit practitioners specifically within cybersecurity, privacy, and ESG (Environmental, Social, Governance). Put simply, we build software for the people who enable trust between businesses.

We’re based in San Francisco, CA, but built as a remote-first company that enables you to do your best work from anywhere. We're backed by top investors including Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, DNX Ventures, Global Founders Capital, Justin Kan, Elad Gil, and more.

We value diversity — in backgrounds and in experiences. We need people from all backgrounds and walks of life to help build the future of audit and advisory. Our team is inclusive, driven, humble and supportive. We are deliberate and self-reflective about the kind of team and culture that we are building, seeking teammates that are not only strong in their own aptitudes but care deeply about supporting each other's growth.

As an early stage start-up employee, you’ll have the opportunity to build out the future of business trust. We make audit practitioners’ lives easier by eliminating up to 50% of their work and giving them better work-life balance. If you share our values and enthusiasm for building a great culture and product, you will find a home here.

About the Role

As a Senior Platform Engineer, Machine Learning, you'll be responsible for building and maintaining the infrastructure that powers our ML solutions in the audit and advisory industry. You'll create scalable, efficient systems for model deployment, monitoring, and continuous improvement, enabling our ML Engineers to deliver impactful solutions. This role is crucial in bridging the gap between ML development and production-ready systems in our rapidly scaling Series B-stage company.

This is an opportunity to join as an early engineer at a company with product-market fit that still has huge amounts of room to grow. We're competing with legacy accounting and audit products that are 20+ years old and have negative NPS, yet do billions in sales and have seen little competition in a decade.

What You'll Do:

• Design and implement infrastructure for ML model management, including training, deployment, and monitoring

• Build and maintain platforms for running ML algorithms at scale

• Develop systems for A/B testing, performance monitoring, and continuous model training

• Create and manage ETL infrastructure to support ML workflows

• Implement best practices for MLOps, including version control for models and datasets

• Collaborate with ML Engineers to optimize model performance and resource utilization

• Ensure the scalability, reliability, and security of ML systems

• Stay current with the latest advancements in MLOps and cloud technologies

• Contribute to the development of internal tools and frameworks to improve ML workflow efficiency

• Be an essential technical contributor at a Series B-stage company as it scales

About You:

• 3-4 years of experience in software engineering, DevOps, or related field with a focus on ML systems

• Experience with ML frameworks

• Experience with cloud platforms, preferably AWS

• Experience with container runtime architectures, preferably Kubernetes

• Proficiency with at least one programming language, preferably Python or Typescript

• Familiarity with CI/CD practices and tools

• Experience with Infrastructure as Code (IaC) tools like Terraform or CloudFormation

• Strong understanding of distributed systems and microservices architecture

• Ability to work in a fast-paced, changing startup environment

Nice to Haves:

• Experience with distributed computing frameworks (e.g., Apache Spark)

• Familiarity with ML experiment tracking tools (e.g., MLFlow, Weights & Biases)

• Knowledge of data versioning and feature store technologies

• Experience with high-volume, real-time data processing

• Familiarity with data security and access control for ML systems

• Experience with cloud cost management and optimization for ML workloads

• Modern web tech stacks consisting of several of the following: GraphQL, NodeJS, Hasura, Postgres

• Background in or exposure to the audit and advisory industry

• Experience presenting technical concepts to non-technical stakeholders

• Experience mentoring or leading small teams

Some of our benefits include:

• Competitive compensation packages with meaningful ownership: $170-185k base + equity
• Healthcare: We offer competitive medical, dental, and vision benefits
• 401k: We offer an optional 401k through Human Interest. We do not offer an employer match at this time.
• Mental health: We offer mental health and therapy benefits through SpringHealth.
• Technology: All employees get a MacBook Pro, as well a monitor, mouse, keyboard (or cash equivalent of those items if you'd like to buy other home office items).
• Unlimited PTO: Take the time off that you need to be the most productive and happy in your work.
• Flexible schedules: We maintain core hours from 9am - 1pm pacific time, and allow people to time shift as necessary around that. We’re extremely flexible with hours and time off, and understand that people need to take care of things from time-to-time. Take the time off you need. We trust our team members to find the right times for them to do their best work.