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Vannevar is a defense technology company building AI to deter our adversaries. In the 21st century, conflict moves at algorithmic speed and foresight equals firepower. Our agentic AI is purpose-built to compete with China—from cross-Strait conflict to gray zone coercion. Trained on the most mission-relevant datasets in defense, our technology models adversary behavior, simulates campaigns, and recommends the best course of action to decision makers. Our AI systems are some of the most trusted in the industry and actively used on the front lines of the Indo-Pacific to keep the peace and save lives. Exceptional technology starts with exceptional people. Vannevar is a small agile team combining world-class engineers with veteran strategists who bring deep expertise in defense and tradecraft. We’re building a company defined by mission impact, user empathy, and disciplined growth. In just three years, we grew from $3M to $80M in ARR, achieved early profitability, and reached unicorn status—proving that disruption doesn’t require an ego, and staying power doesn’t mean standing still. 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 offer Competitive 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 Vannevar is an equal opportunity employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. 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! IMPORTANT NOTICE We are committed to protecting the privacy of all applicants. Official emails from the company will come from an @vannevarlabs.com domain. Under no circumstances will a legitimate representative from our company contact you to request passwords, financial information, or other sensitive personal data. Please be vigilant of potential scams.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
