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Machine learning is core to Vannevar's enrichment capabilities, powering intelligent data extraction, classification, and augmentation at scale. Our ML team builds the services and infrastructure that enable products across Vannevar to leverage state-of-the-art models for mission-critical enrichment workflows. We own the end-to-end ML platform, from training and fine-tuning models to deploying high-performance inference services, and we operate these capabilities in demanding production environments.
You will be a technical leader driving the development of scalable ML services for enrichment. You'll work across the full ML lifecycle, from experimenting with and training models using frameworks like PyTorch, TensorFlow, and Hugging Face, to deploying optimized inference services using ONNX, vLLM, and other deployment libraries. You'll partner with product teams to understand enrichment requirements, architect robust ML pipelines that handle large-scale data processing, and ensure our services meet strict performance and reliability standards in production.
Machine learning is core to Vannevar's enrichment capabilities, powering intelligent data extraction, classification, and augmentation at scale. Our ML team builds the services and infrastructure that enable products across Vannevar to leverage state-of-the-art models for mission-critical enrichment workflows. We own the end-to-end ML platform, from training and fine-tuning models to deploying high-performance inference services, and we operate these capabilities in demanding production environments.
You will be a technical leader driving the development of scalable ML services for enrichment. You'll work across the full ML lifecycle, from experimenting with and training models using frameworks like PyTorch, TensorFlow, and Hugging Face, to deploying optimized inference services using ONNX, vLLM, and other deployment libraries. You'll partner with product teams to understand enrichment requirements, architect robust ML pipelines that handle large-scale data processing, and ensure our services meet strict performance and reliability standards in production.
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Design and build scalable ML services for enrichment workflows, including model training pipelines and high-performance inference APIs
Deploy and optimize models using modern inference libraries and frameworks (ONNX, vLLM, TensorRT, etc.) to achieve low-latency, high-throughput performance
Collaborate with software engineers and product teams to define data requirements, feature engineering strategies, and model evaluation metrics
Build robust monitoring, observability, and evaluation systems to ensure model quality and service reliability in production
Stay current with emerging ML techniques, tools, and best practices, particularly in areas like model optimization, efficient inference, and large-scale data processing
Verified company details for this employer are not available yet.
USD 150000-215000 yearly / year
Full-time
Senior · 5+ years experience
Remote
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