search jobs

Our client, an early-stage, AI-driven startup in the defense industry, is hiring an AI Infrastructure Engineer to join their team in California. The successful candidate will design and scale the foundation of their model training and deployment ecosystem to enable their vision-language-action models to learn from massive real-world datasets and operate seamlessly across both edge and cloud environments.


Responsibilities

• Design and implement pipelines to ingest, transform and store petabytes of multimodal data from their robotic and operator systems.

• Develop tools for dataset exploration, curation, versioning and quality monitoring.

• Build and maintain distributed training infrastructure for large-scale multimodal and foundation model training, both in the cloud and on-premises.

• Implement orchestration workflows to launch, track and debug large-scale model runs.

• Identify and resolve bottlenecks in compute, memory, storage and network performance.

• Collaborate with AI, autonomy and systems teams to support real-time and mission-critical applications.

• Maintain observability and reliability tools for training and inference pipelines.

• Stay up to date with best practices in MLOps, distributed training frameworks and AI infrastructure at scale.

Skillset

• Bachelor’s degree or higher in Computer Science, Electrical Engineering or a related technical field.

• Minimum of 3 years of experience in ML infrastructure, MLOps or large-scale data systems.

• Proven experience with distributed training frameworks (e.g. PyTorch DDP, DeepSpeed, Ray) and workflow orchestration tools (e.g. Kubernetes, Airflow, or equivalents).

• Strong proficiency in Python and hands-on experience with cloud-native infrastructure (AWS, GCP or Azure).

• Solid understanding of data engineering concepts, including ETL pipelines, object storage, data versioning and metadata management.

• Familiarity with containerization technologies (Docker, Kubernetes) and monitoring systems (Prometheus, Grafana).

• Experience optimizing GPU cluster utilization, scaling training jobs and profiling model performance.

• Experience with edge-deployed ML systems, federated training or robotic data collection pipelines is a plus.

• Must have legal authorization to work in the U.S.; certain responsibilities may involve access to export-controlled information.

Benefits

• Salary: $160K – $220K DOE. Exceptional candidates may be considered for higher compensation.

• Performance Bonus.

• Equity.

• Medical, dental and vision insurance.

Our client, an early-stage, AI-driven startup in the defense industry, is hiring an AI Researcher to join their team in California. The successful candidate will combine advanced machine learning research with robotics and defense applications, transforming foundational research into scalable, robust models that operate effectively in unstructured, high-stakes environments - from concept through to deployment.


Responsibilities

• Conduct original research in embodied AI, including reinforcement learning, imitation learning, memory, reward design, vision-language modeling and world modeling.

• Build, test and benchmark large-scale models for perception, decision-making and control in both simulated and physical environments.

• Investigate transfer learning and continual learning across diverse robotic domains.

• Collaborate with engineering, robotics and field teams to integrate research into operational systems.

• Lead research strategy and define the roadmap across key areas of autonomy and machine learning.

• Support field tests and data collection campaigns to evaluate system performance in realistic environments.

Skillset

• PhD in Computer Science, Robotics, Machine Learning or similar.

• Proven publication record in top-tier conferences or journals.

• Deep expertise in reinforcement learning, imitation learning, vision-language models, sim-to-real transfer, world modeling or agentic AI.

• Hands-on experience building and evaluating models for embodied agents or autonomous systems.

• Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow or JAX.

• Experience working with large-scale datasets and high-dimensional sensor inputs.

• Demonstrated ability to take research ideas from concept to deployed prototype.

• Background in DoD, aerospace, or other mission-critical operational deployments is a plus.

• Legal authorization to work in the U.S.; some duties may require access to U.S. export-controlled information.

Benefits

• Salary: $160K – $220K DOE. Exceptional candidates may be considered for higher compensation.

• Performance Bonus.

• Equity.

• Medical, dental and vision insurance.

Our client, an early-stage, AI-driven startup in the defense industry, is hiring an AI Engineer to join their team in California. The successful candidate will design and deploy advanced multimodal models that power the cognitive capabilities of their robotic platforms, playing a key role in shaping the next generation of intelligent defense systems.


Responsibilities

• Design, train, and assess advanced VLA models for robotic platforms.

• Develop scalable architectures for multimodal integration, continual learning and domain adaptation.

• Build dynamic memory, communication and tool-use capabilities for autonomous AI agents.

• Translate state-of-the-art research into real-time, deployable perception and decision-making systems.

• Collaborate with robotics and mission teams to integrate ML pipelines with onboard autonomy.

• Maintain and optimise codebases for training, simulation and real-world inference.

• Evaluate performance and robustness in complex, unstructured and adversarial environments.

• Monitor and incorporate the latest advances in VLMs, reinforcement learning, computer vision and autonomous systems.

• Support field testing and mission operations to validate models under real-world conditions.

Skillset

• PhD or Masters degree or higher in Computer Science, AI or similar.

• At least 2 years of hands-on experience building and deploying AI systems, preferably in agentic AI, robotics, autonomous systems or real-time applications.

• Strong foundation in computer vision, deep learning or multimodal architectures, including VLMs, transformers or autonomous agents.

• Proficiency in Python and PyTorch or TensorFlow. Bonus points for experience with JAX, CUDA, or real-time inference optimisation.

• Experience with distributed training, fine-tuning, and reinforcement learning.

• Demonstrated ability to take research from prototype to production in fast-paced environments.

• Experience with embodied AI systems.

• Background in mission-oriented deployments, such as DoD, aerospace or robotics is a bonus.

Benefits

• Base Salary: $160k - $220k DOE. Exceptional candidates may be considered for higher compensation. 

• Equity.

• Performance bonus.

• Medica, dental and vision coverage.