Shape the future of AI-driven solutions in high-stakes domains by leading the design and implementation of machine learning systems that process diverse data streams—including imagery, video, text, geospatial inputs, and time series. In this role, you'll serve as a technical anchor, translating complex operational needs into scalable, production-grade architectures built on modern cloud platforms and event-driven frameworks.
What You'll Do
- Collaborate with cross-functional teams and stakeholders to define requirements, develop technical strategies, and deliver AI capabilities that directly address mission-critical challenges.
- Design and implement robust machine learning pipelines using Python and frameworks such as TensorFlow and PyTorch, while integrating with systems built in Go, Rust, C++, or JVM-based languages.
- Lead project execution from scoping to deployment, ensuring timely delivery of high-impact deliverables within Agile environments.
- Architect and automate data workflows across microservices and distributed systems, leveraging Kubernetes, Kafka, NATS, or similar technologies to support scalable AI operations.
- Develop and refine models for multimodal data, including full-motion video, synthetic aperture radar, acoustic signals, and other complex sensor inputs.
- Provide technical mentorship to engineers, elevate team practices, and identify reusable components to accelerate future development cycles.
- Engage in fieldwork as needed, working directly with customer teams to understand operational context and ensure solution alignment.
What We Require
- Advanced degree in computer science, machine learning, data science, or a closely related field
- At least 10 years of hands-on experience building and deploying machine learning systems in production
- Strong command of Python and ML libraries, with fluency in at least one systems programming language (Go, Rust, C++, Java, or Scala)
- Proven expertise in algorithm design, data structures, and software engineering best practices—including CI/CD, version control, and debugging in distributed environments
- Experience applying design patterns in cloud-native architectures
- Active Secret security clearance and U.S. citizenship
- Ability to communicate technical concepts clearly to both technical and non-technical audiences through writing, presentations, and direct collaboration
Preferred Background
- Experience with container orchestration platforms like Kubernetes
- Familiarity with messaging systems such as Kafka, RabbitMQ, or NATS
- Track record developing AI agents and automated decision workflows
- Work history in secure government or defense environments
- Exposure to specialized data types such as multi-spectral imagery, sonar, or hardware telemetry
Work Environment
This position supports hybrid work arrangements, with options for full remote work or on-site collaboration in northwest Austin, Texas. Occasional travel (up to 20%) may be required for customer engagements and team coordination.
Compensation & Benefits
Base salary ranges from $200,000 to $250,000 annually, complemented by equity grants and performance-based cash bonuses. Comprehensive benefits include medical, dental, and vision coverage; voluntary insurance options; health and dependent care FSAs; HSA plans; 401(k) with company matching; unlimited paid time off; and paid parental leave.
Our Culture
We foster a high-trust environment where ownership, candor, and mutual respect drive results. Team members are expected to take initiative, support collective goals, and bring sustained focus to meaningful challenges. Work is guided by a shared commitment to impact, personal accountability, and the belief that hard work matters when it serves a greater purpose.
