Machine Learning Engineer

About the Role

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.

What you'll do

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

What we look for

5+ years of experience building and deploying machine learning systems in production environments

Strong proficiency with model deployment technologies (Kubernetes, Ray, etc.) and inference libraries (ONNX, vLLM, TensorRT, or similar). Proficiency with model training frameworks (PyTorch, TensorFlow, Jax)

You've successfully designed and scaled ML services that process large volumes of data and serve predictions with strict latency and throughput requirements

Experience with the full ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring

Solid software engineering skills, including experience with distributed systems, APIs, and cloud infrastructure

You have a passion for building reliable, performant ML systems and understand how they create value for end users

U.S. Person status is required as this position will require the ability to access U.S only data systems

What we offerCompetitive Salary

The salary range for this position is $150,000 - $215,000 + equity Within the range, individual pay is determined by experience, relevant education, and/or training.

Comprehensive Benefits

We’re proud to offer competitive benefits that support our employees. Some key highlights of our benefits package include:

Health, dental, and vision insurance

Remote friendly with WeWork access

Unlimited PTO, shared downtime during the federal holiday calendar, and company-wide off time at the end of each year

401(k) match

Lifestyle & wellbeing stipends

Salary top-up during military reserve duty

Fully paid parental leave

Child and pet care reimbursement during travel