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S32

Software Engineer: ML Robotics Systems

Palo Alto, CA · On-site

$203.60K - $241.30K/yr

S32 is a venture capital firm investing at the frontiers of technology, seeking ML Robotics Systems Engineers who are passionate about building intelligent systems. The role involves making a ...

Peraton

Systems Engineering, SME

Washington, DC · On-site

$146K - $234K/yr

Peraton is seeking a System Engineering SME to support our mission to defend and protect our ... Background in AI/ML-driven DevSecOps practices or intelligent automation for compliance Peraton ...

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How much do intelligent systems engineering jobs pay per year?

As of May 29, 2026, the average yearly pay for intelligent systems engineering in the United States is $142,070.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What is an Intelligent Systems Engineering job?

An Intelligent Systems Engineering job involves designing, developing, and optimizing smart systems that integrate AI, machine learning, and advanced computing. Professionals in this field work on applications such as autonomous systems, robotics, cybersecurity, and biomedical devices. They use data-driven approaches and computational models to enhance decision-making and automation. These roles exist in industries like healthcare, automotive, aerospace, and IoT.

What are the key skills and qualifications needed to thrive in the Intelligent Systems Engineering position, and why are they important?

Successful careers in Intelligent Systems Engineering require a strong background in computer science, control systems, mathematics, and often an advanced degree in engineering or a related field. Proficiency with programming languages (such as Python, C++, or MATLAB), experience with machine learning frameworks, and familiarity with embedded systems and sensor integration are typically expected. Strong analytical thinking, problem-solving skills, and effective collaboration are essential soft skills in this position. These competencies enable professionals to design, develop, and optimize complex intelligent systems that perform reliably in real-world applications.

What are the main challenges faced when working as an Intelligent Systems Engineer?

Intelligent Systems Engineers often encounter challenges such as integrating diverse hardware and software components, ensuring system reliability, and optimizing performance under real-world conditions. They must stay current with rapidly evolving technologies and continuously adapt their solutions to meet new requirements or constraints. Collaboration across multidisciplinary teams, including software developers, hardware engineers, and data scientists, is common and essential for project success. Tackling these challenges develops a well-rounded skill set and provides significant opportunities for professional growth and innovation.

Which companies hire Aiml engineers?

Many technology companies, including large firms like Google, Microsoft, Amazon, and Facebook, hire AI and Machine Learning (Aiml) engineers to develop intelligent systems, data models, and automation solutions. These roles often require knowledge of programming languages such as Python, experience with machine learning frameworks, and a strong background in data science or computer science.
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Intelligent Systems Engineering jobs near you
Principal Engineer, Systems (R5048)

Principal Engineer, Systems (R5048)

Shield AI

San Diego, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:

Shield AI’s Hivemind Platform organization is seeking a Principal Systems Engineer to lead and scale systems engineering excellence across our software-intensive, autonomy-driven platform. This role sits within the Systems Engineering, Integration, and Test (SEIT) organization and is responsible for advancing systems engineering discipline, rigor, and cross-functional alignment across the full lifecycle, from requirements definition through architecture, verification, and assurance.

This individual will play a critical role in shaping how complex autonomous system development capabilities are specified, architected, and validated, with a strong emphasis on model-based systems engineering (MBSE), requirements traceability, and integration of system assurance (including safety) into system design.

What You’ll Do:
  • Systems Engineering Discipline Leadership: Drive the adoption and enforcement of systems engineering best practices across the organization, serving as a technical authority and trusted partner to engineering leadership.
  • Requirements Management & Traceability: Lead the development of structured, testable, and fully traceable system requirements, ensuring end-to-end linkage across architecture, verification, and implementation.
  • Architecture Definition: Define and maintain system architectures using MBSE methodologies and tools (e.g., Cameo), promoting model-centric engineering for system understanding and decision-making.
  • Verification & Validation Planning: Establish comprehensive, executable verification strategies aligned with system requirements and operational use cases, supporting integration and test efforts.
  • System Assurance Integration: Integrate system safety and security assurance considerations into requirements, architecture, and verification to support mission assurance and compliance objectives.
  • Cross-Functional Collaboration: Partner with software architects, product teams, test engineers, and engineering leadership to align system-level decisions/execution across the organization and bridge between SEIT and the broader engineering organization.
Key Outcomes:
  • End-to-End Requirements Traceability Established: System requirements are consistently structured, testable, and fully traceable across architecture, implementation, and verification artifacts.
  • MBSE Adoption at Scale: Model-based systems engineering is broadly adopted, with system architecture and interfaces defined and maintained in a shared, authoritative model.
  • System Assurance Integrated Early: System safety and assurance considerations are embedded in requirements and architecture upfront, reducing late-stage risk and rework.
  • Cross-Functional System Alignment Achieved: Software, product, and Integration & Test teams operate with a clear, shared understanding of system architecture, interfaces, and constraints.
  • Systems Engineering Rigor and Process Maturity Improved: Standardized processes, tools, and artifacts are in place and consistently used across teams, improving quality, predictability, and scalability.
Required Qualifications:
  • 15+ years in Systems Engineering, Architecture, or technical leadership roles
  • Experience in defense or aerospace, ideally with software-intensive unmanned aircraft systems (UAS)
  • Strong background in traceable requirements development, system architecture and interface definition, and V&V planning
  • Hands-on experience with MBSE tools (Cameo Systems Modeler or equivalent) and SysML
  • Proven ability to lead engineering discipline across teams and influence technical direction
  • Bachelor’s degree in engineering or related field
Preferred Qualifications:
  • Experience integrating system safety and assurance practices into engineering workflows
  • Familiarity with certification standards such as MIL-HDBK-516C and CMMC/NIST SP 800-53
  • Advanced degree in engineering or related field
#LI-DM2
#LF

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.

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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.