The ad says“Familiarity with distributed systems, DevOps tooling, and performance tuning”
The ad says“Familiarity with distributed systems, DevOps tooling, and performance tuning”
The ad says“Proficiency in developing full stack applications”
The ad says“Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc”
The ad says“5+ years of combined experience in software engineering and machine learning”
The ad says“Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc”
The ad says“Knowledge of privacy-preserving AI and secure compute environments”
The ad says“Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc”
The ad says“Knowledge of privacy-preserving AI and secure compute environments”
The ad says“5+ years of combined experience in software engineering and machine learning”
The ad says“Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc”
We are seeking a Senior Forward Deployed AI Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments. This role sits at the intersection of machine learning, systems engineering, and deployment optimization, bridging research and real world implementation
You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments
Collaborate closely with customers to scope, deploy, and maintain AI solutions in production environments
Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems
Debug and optimize data pipelines and AI systems running on customer networks
Translate complex, often ambiguous customer requirements into well-scoped technical solutions
Work across the stack—from model inference on consumer hardware to infrastructure automation
Read hardware schematics/logs to identify performance bottlenecks and suggest improvements
Serve as a trusted technical advisor to enterprise clients, representing the engineering team externally
Contribute feedback and insight to internal teams to continuously improve product robustness and usability
Benefits
Grow with us: Equity options so you share in our growth. Build your future as we build ours.
Family first: Parental leave and fertility support for every stage of life. Your family matters here.
Plan your future: A 401(k) to help you save and invest. Secure what’s ahead with confidence.
Stay well: Comprehensive health coverage for body and mind. Because balance fuels great work.
Keep learning: A stipend to explore, study, and sharpen your skills. Growth never stops.
Work anywhere: Remote-first with flexible time off to recharge. Find balance wherever you are.
Preferred experience
Comfortable working in dynamic environments with high customer exposure
Active US Security clearance
5+ years of combined experience in software engineering and machine learning
Exceptional communication skills; able to challenge vague requirements and turn them into actionable plans
Proven track record of deploying and maintaining machine learning/AI systems in production
Experience debugging complex systems involving data pipelines, model inference, and hardware interaction
Strong expertise in ML frameworks such as PyTorch, TensorFlow, ONNX, JAX, etc
Experience deploying models on edge devices or consumer hardware
Familiarity with distributed systems, DevOps tooling, and performance tuning
Proficiency in developing full stack applications
Prior experience in a customer-facing engineering role
Knowledge of privacy-preserving AI and secure compute environments
Master’s degree in a relevant technical discipline
