Machine Learning Engineer, Vannevar
$150-215k
+ Equity
Defense for the digital domain
Be an early applicant
Defense for the digital domain
101-200 employees
Be an early applicant
$150-215k
+ Equity
101-200 employees
Company mission
To build software for the nation's most pressing national security problems.
Role
Who you are
- 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
- We encourage candidates from all backgrounds to apply, even if you don't feel like you're a perfect fit. If you're passionate about contributing to our mission, we'd love to hear from you!
What the job involves
- 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
- 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
Our take
As intelligence analysts work to solve rapidly evolving and increasingly challenging national security problems, modern technology is vital in achieving optimal results as there is no room for failure. Vannevar's innovative foreign text platform delivers solutions to some of today’s most important national security problems.
The company’s workflow platform, Decrypt, uses machine learning and automation to understand, target and respond to foreign actors in ways not previously possible. The platform is a proven success, driving Vannevar’s growth and attracting a $40M OTA contract with the Department of Defense.
Yielding impressive traction so far, the company is using its latest funding round to accelerate strategic initiatives and expand the scope of its technology. This comes after a period of rapid growth and sustained profitability, all suggesting a fruitful future for the company long-term.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
119% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Jan 2023
$75m
SERIES B
Aug 2021
$12m
SERIES A
Total funding: $91.5m
Company benefits
- Health/Dental/Vision Insurance
- Equity + 401(k) Match
- Open PTO + all Federal Holidays and Dec 23-31
- Paid Parental Leave
- 100% Remote - Work From Anywhere in the US
- Flexible Work Environment - You Manage Your Work Day
- Quarterly Off-Site Travel for Team-Building
Company HQ
Palo Alto, CA
Leadership
Nini Hamrick
(President & Co-founder)Former US Intelligence Officer working as a Political & Counterterrorism Programs Analyst. Previous Chief of Staff to the Director of the National Counterterrorism Center, and was a Counterterrorism Analyst for the United States Department of Defense.
Brett Granberg
(CEO)Current Advisor at Lilt. Former Investor at In-Q-Tel and previously worked as a Business Analyst at McKinsey & Company.
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