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AI/ML Engineer

Join NODA AI as an AI/ML Engineer to design intelligent agents for autonomous systems in a hybrid work environment.

Location
Austin
Compensation
Not disclosed
Level
mid
Type
full time · Hybrid

Posted by employer 1 week ago

First seen on Joblaze 1 month ago

Last verified on the company career page 1 day ago

Apply at NODA AI → Save job Scanned from nodaintelligence.ai

AI in the day-to-day

AI/ML Engineers design and implement AI agents that bridge mission intent with real-world execution.

Requirements

Experience
3+ years

Not disclosed in this posting: compensation, visa sponsorship.

Benefits

401k Match Mental Health Resources Unlimited PTO Equity/Stock Options Health Insurance Parental Leave

Joblaze summary

The AI/ML Engineer at NODA AI focuses on designing and implementing intelligent agents that facilitate adaptive mission planning for unmanned systems across various domains. Key skills include proficiency in Python, experience with large language models, and the ability to optimize AI for edge computing environments. This role is ideal for professionals with at least three years of experience in AI/ML applications, particularly those with a background in robotics or autonomous systems. NODA AI, a veteran-owned company, emphasizes innovation and collaboration in developing cutting-edge autonomous technologies.

Joblaze insights

  • Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on NODA AI's careers page October 27, 2026.
  • AI/ML appears in 52.2% of 467 comparable mid ai/ml roles in United States; ROS appears in 0.2% of 467 comparable mid ai/ml roles in United States.

Quick facts

Is the AI/ML Engineer role remote?
It's hybrid — NODA AI expects some on-site time in Austin.
How much experience is required?
At least 3 years of relevant experience for this AI/ML Engineer role.
Where is the role based?
NODA AI is hiring for this position in Austin.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, LLM, LangChain, PyTorch, Python, ROS.
What seniority level is this role?
NODA AI targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this AI/ML Engineer role at NODA AI.

From the original posting

AI/ML Engineer – NODA AI

Location: Austin, TX (Hybrid on-site, with up to 20% travel)
Clearance Requirement: U.S. Citizen with the ability to obtain a security clearance

Our AI/ML Engineers are at the cutting edge of autonomous intelligence, designing and implementing AI agents that seamlessly bridge mission intent with real-world execution through advanced reasoning frameworks and multi-domain orchestration capabilities.

The Role

We are seeking an AI/ML Engineer to design and implement intelligent agents that drive adaptive mission planning and orchestration across multi-domain unmanned systems. This role focuses on LLM orchestration frameworks, agent reasoning systems, and the deployment of AI models to edge computing environments on autonomous vehicles.

You will build systems that translate high-level mission intent into actionable autonomous behaviors, dynamically adapt plans as environments change, and provide explainable reasoning to human operators. Your work will integrate directly with our ROS autonomy stack while ensuring reliable AI performance on resource-constrained edge hardware.

Key Responsibilities

  • Design and implement LLM orchestration frameworks for mission planning and task decomposition across heterogeneous vehicle fleets

  • Develop agent reasoning systems that bridge high-level mission objectives with executable autonomy commands

  • Optimize large and quantize language models and agent frameworks for deployment on edge computing hardware (Jetson, companion computers)

  • Manage the full lifecycle of AI agents including model versioning, prompt engineering, tool integration, and memory management

  • Implement human-in-the-loop workflows that provide transparent, explainable AI reasoning to operators

  • Integrate AI reasoning outputs with autonomy middleware (e.g., ROS 2) to enable seamless mission execution across heterogeneous

  • Build evaluation, monitoring, and logging systems to track agent performance, reliability, and cost in operational environments

  • Develop safe deployment and rollback practices for AI agents in mission-critical scenarios

  • Collaborate with autonomy engineers to ensure AI-generated plans are executable and safe across multi-domain platforms

  • Validate agent behaviors through simulation-in-loop testing before field deployment

  • Design AI systems that maintain effectiveness in denied, degraded, and contested communication environments

Required Qualifications

  • 3+ years of experience in production AI/ML applications with emphasis on LLM deployment and orchestration

  • Proficiency in Python and modern AI/ML frameworks (PyTorch, Transformers, LangChain, or equivalent orchestration tools)

  • Experience with model optimization, quantization, and deployment to edge computing environments

  • Understanding of distributed systems and real-time AI inference requirements

  • Familiarity with MLOps practices, including model versioning, monitoring, and lifecycle management

  • Knowledge of prompt engineering, agent framework design, and multi-step reasoning systems

  • Experience with constraint solving, planning algorithms, or symbolic reasoning approaches

  • Due to the nature of the position, U.S. citizenship is required due to ITAR regulations, along with the ability to obtain and maintain a DoD security clearance.

 

Preferred Qualifications

  • Experience with multi-agent coordination frameworks and distributed AI reasoning systems

  • Background in robotics or autonomous systems integration (ROS2ROS 2, navigation stacks, sensor fusion)

  • Familiarity with reinforcement learning for planning and decision-making applications. Understanding; understanding of secure coding practices and adversarial robustness in AI-driven systems.

  • Experience deploying AI models to embedded hardware (Jetson, Raspberry Pi, or similar edge devices)

  • Exposure to simulation-in-loop and hardware-in-loop testing environments

  • Knowledge of autonomous vehicle domains (UAVs, USVs, UUVs) and associated protocols

  • Background in structured data preparation and feature engineering for AI ingestion

  • Contributions to open-source AI or robotics projects

  • Experience contributing to mission assurance and safety cases, including field-readiness reviews

  • Experience collaborating with security and compliance teams on logging, auditability, and data-handling requirements for fielded AI systems

Skills and Attributes

  • Systems thinker able to connect AI reasoning outputs with real-world autonomous execution

  • Fast learner with adaptability to rapidly evolving AI/ML frameworks and methodologies

  • Safety-focused mindset with commitment to explainable, reliable AI in mission-critical environments

  • Thrives in ambiguous, mission-driven problem spaces requiring creative AI solutions

  • Collaborative team player comfortable working across AI, autonomy, and field operations disciplines

  • Detail-oriented approach to AI system validation, testing, and performance optimization Systems thinker able to connect AI reasoning outputs with real-world autonomous execution

  • Fast learner with adaptability to rapidly evolving AI/ML frameworks and methodologies

  • Safety-focused mindset with commitment to explainable, reliable AI in mission-critical environments

  • Thrives in ambiguous, mission-driven problem spaces requiring creative AI solutions

  • Collaborative team player comfortable working across AI, autonomy, and field operations disciplines

  • Detail-oriented approach to AI system validation, testing, and performance optimization

  • We offer premium medical, dental, and vision coverage with zero paycheck premiums for you and your family

  • Equity grants for new hires

  • Unlimited PTO

  • 11 Paid holidays

  • Generous Parental Leave

  • FSA

  • DCFSA

  • HSA

  • Professional Development Opportunities

  • Access to One Medical

Growth Path at NODA

AI/ML Engineer → Senior AI/ML Engineer → Staff AI/ML Engineer → Principal Engineer. Final leveling will be determined at the offer stage based on scope demonstrated in interviews, prior impact, and calibration to NODA’s career ladder.

 
 
 

Standard company text repeated across NODA AI's postings is omitted here.

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