Shield AI

Senior Software Engineer, Perception (R5420)

Shield AI$163K — $244K *
Aerospace & Defense
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in machine learning with a Bachelor's, or 4 years with a Master's, or 2 years with a PhD; or equivalent experience.
  • Strong foundation in machine learning principles.
  • Experience training and deploying computer vision models in production.
  • Deep understanding of 3D vision algorithms and problems.
  • Proficiency with ML frameworks like PyTorch and TensorFlow.
  • Expertise in using TensorRT and ONNX for model deployment.
  • Skilled in C++ and Python; strong analytical and problem-solving abilities.

Responsibilities

  • Design, train, and maintain advanced vision models to enhance autonomous system perception.
  • Build scalable data pipelines and evaluation loops to improve model performance.
  • Deploy and optimize ML models for use on embedded hardware.
  • Apply machine learning techniques to resolve challenges in perception and autonomy for various aerial systems.
  • Translate leading research into production-ready capabilities, ensuring robustness and efficiency.
  • Collaborate with cross-functional teams to integrate ML into operational autonomous systems.
  • Develop benchmarks and evaluations to monitor model performance and guide future enhancements.

Benefits

  • Health, dental, and vision insurance.
  • Retirement savings plan with employer match.
  • Generous paid time off and holiday schedule.
  • Professional development and training opportunities.
  • Equity options for full-time employees.
Full Job Description
The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities.

In this role, you'll develop and deploy advanced machine learning models that solve real-world perception challenges for autonomous systems. You'll own major features from model development through deployment, working closely with machine learning researchers, perception engineers, autonomy engineers, and platform teams to bring cutting-edge AI capabilities into production. This is an ideal opportunity for engineers who enjoy solving difficult perception problems while building reliable, production-ready ML systems that operate on autonomous platforms in complex operational environments.

What You'll Do:

Model Development - Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems.

Data Pipelines & Model Training - Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks.

Model Deployment & Optimization - Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks.

Perception & Autonomy Applications - Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments.

Research-to-Production - Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability.

Cross-functional Collaboration - Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems.

Model Evaluation & Validation - Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements.

Continuous Improvement - Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery.

Required Qualifications:

  • Typically requires a minimum of 5 years of related experience with a Bachelor's degree; or 4 years and a Master's degree; or 2 years with a PhD; or equivalent work experience.


  • Prioficiency of machine learning fundamentals.


  • Experience training an deploying ML models for computer vision in a production setting.


  • Strong understanding of 3D vision problems/algorithms.


  • Experience with machine learning frameworks such as PyTorch and TensorFlow.


  • Demonstrated expertise in deploying models using TensorRT and ONNX.


  • Proficiency in C++ and Python.


  • Strong analytical and problem-solving skills, with the ability to translate research into practical applications.
  • Ability to obtain a SECRET clearance


Preferred Qualifications:

  • Experience with developing autonomous systems for defense customers.


  • Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.


  • Contributions to open-source projects in machine learning or computer vision.


  • Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).


$163,200 - $244,800 a year

#LI-DS-1

#LC

Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

About Shield AI

Shield AI is a defense technology company that develops artificially intelligent systems for military applications. The company was founded in 2015 by Brandon Tseng, Ryan Tseng, and Andrew Reiter, and is headquartered in San Diego, California. Shield AI's products include autonomous drones and software that can be used for reconnaissance, surveillance, and other military operations. The company's mission is to reduce the number of military casualties by providing soldiers with better intelligence and situational awareness. Shield AI has received funding from a number of investors, including Andreessen Horowitz and Founders Fund.
Learn more about Shield AI
Size
200 employees
Industry
Founded
2015

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