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Entry Level Intelligent Systems Engineering Jobs

S32

Software Engineer: ML Robotics Systems

Palo Alto, CA · On-site

$203K - $241K/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 ...

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Entry Level Intelligent Systems Engineering information

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$40.5K

$86.4K

$142.5K

How much do entry level intelligent systems engineering jobs pay per year?

As of Jul 30, 2026, the average yearly pay for entry level intelligent systems engineering in the United States is $86,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $103,500.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Intelligent Systems Engineering vs Entry Level Robotics Engineering?

AspectEntry Level Intelligent Systems EngineeringEntry Level Robotics Engineering
Required CredentialsBachelor's in Engineering, Computer Science, or related field; knowledge of AI, machine learning, and systems integrationBachelor's in Mechanical, Electrical, or Robotics Engineering; knowledge of control systems, sensors, and automation
Work EnvironmentDesigning and developing intelligent systems, software integration, testing in labs or office settingsBuilding, testing, and maintaining robotic systems, often in labs or manufacturing environments
Industry UsageTech companies, AI firms, defense, and automation industriesManufacturing, automation, aerospace, and research labs

Entry Level Intelligent Systems Engineering focuses on developing and integrating AI-driven systems, while Entry Level Robotics Engineering emphasizes designing and building robotic devices. Both roles require a strong technical background and often overlap in skills like programming and systems analysis, but they serve different primary functions within technology and engineering sectors.

What are the key skills and qualifications needed to thrive as an Entry Level Intelligent Systems Engineer, and why are they important?

To thrive as an Entry Level Intelligent Systems Engineer, you need a solid background in computer science, mathematics, and engineering principles, often evidenced by a relevant bachelor's degree. Familiarity with programming languages (such as Python or C++), machine learning frameworks, and simulation tools is typically required. Strong analytical thinking, teamwork, and effective communication skills help you collaborate on complex projects and solve interdisciplinary problems. These competencies are crucial for designing, implementing, and optimizing intelligent systems that meet real-world needs.

What is an intelligent systems engineering salary?

Entry-level intelligent systems engineering salaries typically range from $70,000 to $90,000 annually, depending on location, education, and industry. Professionals in this field often work with programming, robotics, and AI tools, with higher salaries available as experience and certifications increase.

What is an entry level intelligent systems engineer?

An entry level intelligent systems engineer is a professional who works on designing, developing, and implementing intelligent systems, such as artificial intelligence, machine learning algorithms, and robotics, typically at the start of their career. They often assist senior engineers in creating software or hardware systems that can perceive, reason, and make decisions. Their responsibilities might include coding, testing, debugging, and collaborating with multidisciplinary teams to solve real-world problems using intelligent technologies.

What types of projects and technologies do entry-level Intelligent Systems Engineers typically work on in their first year?

Entry-level Intelligent Systems Engineers often start by contributing to projects involving robotics, machine learning models, or embedded systems. They may be responsible for tasks such as developing algorithms, testing prototypes, analyzing system performance, or troubleshooting hardware/software integration issues. Team collaboration is common, especially with senior engineers, data scientists, and software developers, providing excellent learning opportunities. Exposure to a variety of technologies and real-world applications helps new engineers quickly build foundational skills and understand the broader impact of intelligent systems in industries like healthcare, automotive, or manufacturing.

What engineer makes $500,000 a year?

While most entry-level intelligent systems engineering roles do not pay $500,000 annually, senior engineers with extensive experience, specialized skills in AI, machine learning, or robotics, and leadership responsibilities can reach or exceed this level through bonuses, stock options, and profit sharing. Such compensation is typically associated with senior or executive-level positions in large technology companies or startups.

Which 5 jobs will survive AI?

Entry Level Intelligent Systems Engineering roles are likely to persist as they require specialized knowledge in designing, developing, and maintaining AI systems, which involves skills in programming, data analysis, and understanding complex algorithms. Jobs that involve creative problem-solving, human interaction, and oversight of AI applications, such as AI system testers, technical support specialists, and AI ethics analysts, are also expected to remain in demand. Continuous learning and certification in relevant tools like machine learning frameworks can help ensure job security in this evolving field.

Are there any entry-level AI jobs?

Entry-level AI jobs, such as positions in intelligent systems engineering, are available for candidates with foundational knowledge in programming, data analysis, and machine learning. These roles often require familiarity with tools like Python, TensorFlow, or similar frameworks and may include internships or junior positions designed for recent graduates or those new to the field.
More about Entry Level Intelligent Systems Engineering jobs
What are the most commonly searched types of Intelligent Systems Engineering jobs? The most popular types of Intelligent Systems Engineering jobs are:
What job categories do people searching Entry Level Intelligent Systems Engineering jobs look for? The top searched job categories for Entry Level Intelligent Systems Engineering jobs are:
Entry Level Intelligent Systems Engineering jobs near you
Infographic showing various Entry Level Intelligent Systems Engineering job openings in the United States as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $86,381 per year, or $41.5 per hour.

Intelligent Systems Engineer II

ClarkDietrich

West Chester, OH • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

ClarkDietrich rating

7.6

Company rating: 7.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Job description

Do you have a strong work ethic and the desire to join an organization that invests in its people through cross-training and development? ClarkDietrich fosters a work-life balance and offers competitive compensation and benefits. Join the ClarkDietrich team by applying to the Intelligent Systems Engineer II position.
Position Summary
The Intelligent Systems Engineer II will support the design, development, testing, and implementation of intelligent software systems that combine artificial intelligence, machine learning, data engineering, automation, cloud services, and modern software development practices.
This role is a hands-on technical engineering position. The Intelligent Systems Engineer II will work under the direction of the Technical Manager and will be responsible for solving assigned technical problems, contributing to system design and implementation, building reliable components, and supporting the development of scalable intelligent applications.
This position is not expected to independently define business problems, own business-facing strategy, or directly lead stakeholder discovery. Instead, the role will translate technical direction, requirements, and priorities provided by the Technical Manager into practical engineering solutions.
Role Scope and Expectations
  • Work primarily as a technical contributor under the direction of the Technical Manager.
  • Solve assigned technical problems at the system, software, data, AI, and integration levels.
  • Support implementation, testing, documentation, and production-readiness of intelligent systems.
  • Escalate risks, blockers, tradeoffs, and unclear requirements to the Technical Manager in a timely manner.
  • Participate in technical discussions and provide input, while business-facing prioritization and solution direction remain coordinated through the Technical Manager or designated leadership.

Key Responsibilities
Intelligent Systems Development
  • Design, develop, test, and maintain components of AI-enabled software systems and automation workflows.
  • Build technical solutions using machine learning models, large language models, data pipelines, APIs, databases, and cloud services.
  • Implement assigned features, services, integrations, and backend logic based on technical direction from the Technical Manager.
  • Support prototype development, technical validation, and transition of approved solutions into stable, production-ready implementations.
  • Research and evaluate technologies when assigned, and provide technical findings and recommendations to the Technical Manager.

Machine Learning and Applied AI
  • Support the development, testing, evaluation, and improvement of machine learning and AI-enabled solutions.
  • Assist with model training, validation, performance testing, accuracy measurement, and error analysis.
  • Prepare and process structured, semi-structured, and unstructured data for use in intelligent systems.
  • Help create evaluation methods to measure consistency, reliability, accuracy, and technical performance.
  • Work with the Technical Manager to ensure AI outputs are reviewed, explainable where needed, and aligned with approved technical standards.

Data Engineering and System Integration
  • Build and maintain data pipelines for collecting, cleaning, transforming, and organizing technical and operational data.
  • Develop backend services, APIs, and integration components that connect intelligent systems with internal applications.
  • Support data quality, traceability, security, and maintainability across assigned technical work.
  • Work with databases, file storage, cloud services, and application interfaces as needed.
  • Document data flows, integration logic, assumptions, and technical limitations.

Cloud and Software Engineering
  • Develop cloud-supported applications and services using modern software engineering practices.
  • Participate in version control, code reviews, testing, deployment, environment management, and release support.
  • Support CI/CD pipelines, containerization, automated testing, and monitoring where applicable.
  • Improve performance, reliability, scalability, maintainability, and cost efficiency of assigned systems.
  • Follow team standards for code quality, documentation, security, and operational support.

Collaboration and Technical Execution
  • Work under the leadership of the Technical Manager to execute assigned technical priorities.
  • Collaborate with software developers, engineers, data contributors, product contributors, interns, and IT stakeholders as needed.
  • Ask clarifying technical questions and raise risks, blockers, and tradeoffs early.
  • Participate in design reviews, technical planning sessions, and implementation discussions.
  • Provide clear status updates, technical notes, and documentation for assigned work.

Required Qualifications
  • Degree or equivalent experience in computer science, engineering, artificial intelligence, machine learning, data science, software engineering, or a related technical field.
  • Strong programming skills, preferably in Python and modern backend development.
  • Experience with applied AI, machine learning, data processing, automation, or intelligent software systems.
  • Experience working with APIs, databases, backend services, and software integrations.
  • Familiarity with cloud platforms, preferably AWS.
  • Understanding of software engineering practices, including version control, testing, documentation, and deployment.
  • Ability to understand technical direction and convert it into working software components.
  • Strong analytical, problem-solving, communication, and collaboration skills.
  • Ability to work in a structured technical team environment under the guidance of a Technical Manager.

Preferred Qualifications
  • Advanced degree or research experience in artificial intelligence, machine learning, engineering, optimization, data science, or computational methods.
  • Experience with large language models, OCR, retrieval-augmented generation, vector databases, intelligent agents, or document intelligence systems.
  • Experience applying AI or machine learning to engineering, construction, manufacturing, automation, or complex operational workflows.
  • Experience with AWS services such as S3, Lambda, ECS, ECR, API Gateway, RDS, DynamoDB, Bedrock, Textract, SageMaker, or similar technologies.
  • Experience with CI/CD, GitHub, containers, automated testing, and modern software release practices.
  • Familiarity with technical design workflows, engineering software, or knowledge-intensive business processes is a plus.

Key Success Outcomes
  • Deliver assigned technical components for intelligent systems and AI-enabled applications.
  • Support data pipelines, model evaluation, backend services, APIs, and cloud-based implementation work.
  • Contribute to improving system reliability, maintainability, performance, and scalability.
  • Follow technical direction from the Technical Manager and execute work with increasing independence.
  • Communicate progress, risks, and technical findings clearly and consistently.
  • Help strengthen the team's software, data, AI, and cloud engineering practices.

Reporting and Collaboration
This role reports to the Technical Manager within the software development or digital technology function.
The position is primarily responsible for hands-on technical execution and implementation.
Business requirements, stakeholder priorities, and solution direction will be coordinated through the Technical Manager or designated leadership.
CLARKDIETRICH BENEFITS INCLUDE:
Full benefits package (Medical, Dental, Vision, Flexible Spending Accounts and Life Insurance)
401(k) with company match
Annual Incentive
Paid Time Off
Tuition Reimbursement
Professional Certification Reimbursement Program
Community Service Day

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