Job details

Senior Platform Engineer, Machine Learning

About Us:

Fieldguide is 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. Fieldguide’s 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 at Fieldguide.

About the Role:

As a Senior Platform Engineer, Machine Learning, at Fieldguide, 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

More about Fieldguide:

Fieldguide is a values-based company. Our values are: