About the job
Vannevar Labs is at the forefront of defense technology, developing innovative AI solutions to outmaneuver our adversaries. In an era where conflict unfolds at algorithmic speed, having the foresight to anticipate actions is crucial. Our advanced AI systems are specifically designed to engage in competition with China, addressing challenges from cross-Strait tensions to gray zone confrontations. Leveraging meticulously curated datasets relevant to defense, our technology can model adversary behaviors, simulate strategic campaigns, and provide actionable recommendations for decision-makers. Our AI solutions are among the most reliable in the industry, actively employed on the front lines of the Indo-Pacific to safeguard peace and preserve lives.
Exceptional technology is a product of exceptional talent. At Vannevar, we foster a small, agile team that merges world-class engineering talent with seasoned strategists, each bringing extensive expertise in defense and tradecraft. Our mission-driven approach emphasizes user empathy and disciplined growth, as evidenced by our rapid ascent from $3 million to $80 million in annual recurring revenue (ARR) within just three years, achieving profitability and unicorn status.
About the Role
Machine learning is a cornerstone of Vannevar's enrichment capabilities, facilitating intelligent data extraction, classification, and augmentation on a large scale. Our ML team is responsible for building the services and infrastructure that empower our products to utilize cutting-edge models for essential enrichment workflows. We oversee the complete ML lifecycle, from training and fine-tuning models to deploying high-performance inference services, operating within demanding production environments.
As a technical leader, you will spearhead the creation of scalable ML services for enrichment. Your responsibilities will encompass the entire ML lifecycle—from experimenting with and training models using frameworks such as PyTorch, TensorFlow, and Hugging Face, to deploying optimized inference services utilizing ONNX, vLLM, and various deployment libraries. You will collaborate with product teams to grasp enrichment requirements, architect robust ML pipelines to manage large-scale data processing, and ensure our services uphold stringent performance and reliability standards in production.
Responsibilities
- Design and implement scalable ML services for enrichment workflows, including model training pipelines and high-performance inference APIs.
- Deploy and optimize models using contemporary inference libraries and frameworks (ONNX, vLLM, TensorRT, etc.) to achieve low-latency and high-throughput performance.
- Work closely with software engineers and product teams to establish data requirements, feature engineering strategies, and model evaluation metrics.
- Develop robust monitoring solutions to ensure operational excellence and reliability.