Senior MLOps Engineer

Vannevar Labs builds next generation defense software for the public servants keeping our country safe. As a team, we exist because we believe in public service, and we think that our democracy and government improve only if we put serious, collective effort into improving them, including the technology our government uses. This mission has become urgent. Ukraine is engaged in a war for survival with Russia. China regularly flies nuclear-capable bombers into Taiwan and Japan’s airspace. The US and our allies are fighting a war of deterrence with woefully outdated technology. We build software to support these missions, including providing battlefield information to allies, identifying malign activity, and helping the US deter and deescalate conflict. We are a profitable growth startup with some of the best defense investors in the world, including General Catalyst, DFJ Growth, Point72, and enterprise tech investors Costanoa and Felicis. 

Senior MLOps Engineer 

We are looking for an MLOps engineer to help identify build new machine learning products within our multi-terabyte data lake. You’ll be part of a cross-functional team that includes deep learning experts, software engineers, and officers from all branches of the military. We also do something common in Silicon Valley tech companies but radical in the defense space: we develop and test products side-by-side with our users, including on US military bases and remote locations abroad. Our engineering culture is about empathizing with users and building software products that deliver maximum mission impact. 

As a Senior member of the team your decisions today will have a large impact on the company today and into the future. We believe that simple systems are easier to understand, maintain, and scale - we prefer pragmatic, product-centric solutions. You are innovative: willing to take risks, think critically about novel solutions, and advocate for your ideas while seeking feedback and collaboration. You will be making trade-offs as you work to ensure that our systems are prepared to scale — being able to effectively communicate these trade-offs with your teammates is a must.  

What You’ll Do

• Write data pipeline workflows for building features and training models  
• Build robust and scalable machine learning infrastructure for performing model inference in batch and real-time 
• Optimize LLM deployment and inference 
• Design and build software to support ML model iteration and production deployment such as model repositories and model monitoring software 
• Work with development teams …