This is a hybrid role to be based in our San Francisco office.
Our Engineering Team architects the underlying core services, platform infrastructure, dev toolkits, core algorithms, machine learning models, packaged end-user apps, and app store marketplace. Instabase engineers are excited to solve hard problems for complex organizations and are self-starters from day one. As part of our Machine Learning Infrastructure Team, you’ll design and develop the next generation of machine learning products at Instabase. We are bridging the human-machine gap in ML, enabling humans to understand, debug, and fine-tune models, all the while deploying and managing these models at large scales (millions of requests per month).
As a Software Engineer working on Instabase products, you’ll build intuitive applications that empower our customers to leverage the latest technologies in AI/ML to tackle their hardest document understanding problems. Our tools and platform shine when facing highly unstructured documents. Our infrastructure is written in Go, Python and operates using the micro-services model. We use Docker and Kubernetes for our deployments.
What you'll do
- Design and implement architectures for using, testing, and training models at scale, both in the cloud and on customer premises using Kubernetes.
- Design and develop and contribute to scalable distributed systems infrastructure that power the ML/AI infrastructure.
- Dive into the complexities of real-time data processing and develop strategies to ensure that our systems can efficiently handle the dynamic outputs of generative AI models.
- Design and implement best practices for model management and deployment.
- Create products around models that make it easy for the customer to use and understand machine learning models and approaches.
- Work with both internal and external developers / data scientists to bring models into Instabase that are then used by customers to solve use cases.
- Troubleshoot production issues and contribute to improving our platform stability.
About you
- You have 3+ years experience as a software engineer.
- You enjoy thinking about how the end user / customer interacts with and understands models.
- You like getting to the bottom of deep, complex problems. You aren’t satisfied with “it works” until you understand why.
- You are familiar with both distributed systems and data science, and enjoy thinking about how the two are built together.
- You have experience with proper software engineering best practices.
- Experience with Kubernetes, existing ML scaling techniques and model training/serving technologies like AnyScale Ray, vLLM, AWS Sagemaker preferred
- Experience with machine ]learning (ML) and artificial intelligence (AI) in the space of document understanding preferred
The on-target earnings (OTE) for this role is $175,000 to $190,000 + equity and US benefits. The actual pay may vary based on factors such as location, experience and skills.
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