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Virginia, United States
Hybrid
About Obviant
The defense market is surging, but the data that drives it hasn't kept up. Companies, government, and investors are forced to perform heavily manual processes and piece together hundreds of disparate sources to make critical decisions for national security.
Obviant is building the data source of truth to power the entire defense acquisition system. We fuse information from thousands of sources (structured and unstructured) to provide a cohesive picture of budget, programs, the organizations running them, and much more. We're growing quickly on the back of strong customer satisfaction at top-tier accounts, backed by leading venture funds, and advised by veterans from national security and the technology industry.
The Role
At Obviant, you'll build the ML systems that turn sprawling, unstructured defense and government data into a knowledge graph our customers can actually reason over. As an AI/ML Engineer, you'll own problems end to end — designing transformer-based extraction and entity-resolution pipelines, adapting language models to a specialized domain, and helping shape the ontology that underpins the product. You'll work on a small team where your decisions show up in the product within weeks, alongside engineers and domain experts who know the mission cold. We care less about buzzword coverage than about people who can take an ambiguous, messy problem and make it rigorous and shippable.
Responsibilities
You’ll design and implement models tackling complex, domain-specific challenges in taxonomy extraction/generation, entity resolution, and pattern recognition
Develop multi-class classification systems
Knowledge graph construction and analysis
Work on Natural Language Processing and semantic understanding problems such as topic modeling
Tackle document clustering, classification, and summarization problems
Build and optimize robust data pipelines that process mission-critical information at scale
Qualifications
Required
8+ years of experience building and deploying ML models in production environments
Strong background in machine learning and deep learning methodologies
Demonstrated experience in applied research and development
Track record of turning complex requirements into elegant, scalable solutions
Experience with NLP, semantic retrieval, or large language models
Experience working with large-scale datasets and complex data pipelines
Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
Comfortable with the pace and impact of a fast-growing startup
Has led, deployed and maintained AI and ML infrastructure and products into multiple disparate environments
Nice to Have
National security, govtech, or defense experience is welcome but not required
Prior experience at a defense-focused data, analytics, or intelligence platform
Our Working Style
Mission orientation: the work matters, and we want teammates who feel that weight
Perseverance and endurance - Hard problems are worth solving, and solving them can take a long time. There is no such thing as exhausting all options, it’s just time to look for new ones.
High ownership: you can expect autonomy and accountability in equal measure
Directness: we communicate with candor and assume good intent
No ego: You’re really good at what you do, but it speaks for itself. High output and humility go hand in hand here
Comfortable with uncertainty - We’re deliberate about setting goals, but we’re comfortable changing course and dealing with discomfort to get there.
Bias toward action: we'd rather move and course-correct than wait for perfect information
Integrity is never negotiable – Transparency, honesty, and respect comes above all else.
Compensation and Benefits
Competitive base salary commensurate with experience
Equity stake in a well-funded, fast-growing company
Health, dental, and vision coverage
Flexible schedule and vacation time
In-office culture headquartered in Arlington, VA, with flexibility when you need it