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Machine Learning Electrical Engineering Jobs (NOW HIRING)

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Machine Learning Electrical Engineering information

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$50.5K

$111.1K

$168K

How much do machine learning electrical engineering jobs pay per year?

As of Jun 4, 2026, the average yearly pay for machine learning electrical engineering in the United States is $111,091.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Electrical Engineer, and why are they important?

To thrive as a Machine Learning Electrical Engineer, you need a strong background in electrical engineering principles, mathematics, and proficiency in programming languages such as Python or MATLAB, often supported by a relevant degree. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch), embedded systems, and data analysis tools is typically required, along with certifications in AI or data science being advantageous. Analytical thinking, creativity, and effective communication are essential soft skills for developing innovative solutions and collaborating across multidisciplinary teams. These competencies are crucial for designing intelligent systems that bridge hardware and software, driving advancements in smart technologies.

How do machine learning engineers and electrical engineers typically collaborate on projects involving smart hardware devices?

In projects involving smart hardware devices, machine learning engineers and electrical engineers often work closely from the initial design phase through deployment. Electrical engineers focus on designing and optimizing the hardware—such as sensors, circuits, or embedded systems—while machine learning engineers develop algorithms that process data collected by these devices. Collaboration is crucial for ensuring that the hardware can support the computational requirements of the models, and vice versa. Regular meetings and cross-functional teams are common, allowing both sides to address challenges like data quality, power consumption, and real-time processing. This teamwork not only ensures successful product development but also provides ample learning opportunities for professionals in both fields.

What is machine learning in electrical engineering?

Machine learning in electrical engineering involves applying algorithms and statistical models to analyze and interpret data from electrical systems. This can include tasks like fault detection, power grid optimization, signal processing, and automation of control systems. Electrical engineers use machine learning to improve system reliability, efficiency, and to develop smart devices. The integration of machine learning enhances traditional engineering methods by enabling predictive maintenance, adaptive controls, and intelligent decision-making.

Can electrical engineers work in machine learning?

Electrical engineers can work in machine learning by applying their knowledge of signal processing, systems, and hardware to develop algorithms, sensors, and embedded systems. Many roles require programming skills in languages like Python or MATLAB and understanding of data analysis and neural networks. Transitioning often involves gaining expertise in machine learning frameworks and data science concepts.

What is the difference between Machine Learning Electrical Engineering vs Electrical Engineering?

AspectMachine Learning Electrical EngineeringElectrical Engineering
Required CredentialsBachelor's or Master's in Electrical Engineering, plus knowledge of machine learningBachelor's or Master's in Electrical Engineering, focus on circuits, systems, and power
Work EnvironmentResearch labs, tech companies, AI-focused projectsPower plants, manufacturing, infrastructure, and electronics industries
Industry UsageAI integration in electrical systems, smart devices, automationPower systems, electronics, telecommunications, control systems

Machine Learning Electrical Engineering combines electrical engineering principles with machine learning techniques to develop intelligent systems. In contrast, Electrical Engineering focuses on designing and maintaining electrical systems and infrastructure. While both roles require a strong foundation in electrical concepts, Machine Learning Electrical Engineering emphasizes AI and data-driven solutions, often within tech and research environments, whereas Electrical Engineering covers a broader range of electrical systems across various industries.

Senior Machine Learning Research Scientist - Secure AI Lab

Senior Machine Learning Research Scientist - Secure AI Lab

Software Engineering Institute

Arlington, VA • On-site

$113.50K - $144.60K/yr

Other

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


Job description

Senior Machine Learning Research Scientist

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.

As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we:

  • build real-world, mission-scale AI capabilities through solving practical engineering problems
  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities
  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities
  • identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape

Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.

As a Senior Machine Learning Research Scientist, you will specialize in conducting research into the vulnerabilities of AI and ML algorithms and securing against those vulnerabilities.

The Secure AI Lab within the SEI's AI Division focuses on improving the security and robustness of AI systems. As part of the world-class research community at Carnegie Mellon University, the Secure AI Lab conducts and applies cutting-edge research to protect AI systems from adversaries who aim to manipulate the system to learn, do, or reveal something it isn't supposed to.

The Secure AI Lab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:

  • Counter AI Research: Study threat models targeting AI and ML algorithms, understand the behaviors of AI algorithms, identify weak points, and design novel ways to subvert AI and ML systems.
  • AI and ML Algorithm Defense Research: Create practical mitigations and defenses for observed attacks affecting AI and ML algorithms and evaluate the effectiveness of defensive techniques.
  • Applied Adversarial Machine Learning: Advance the state of the art in adversarial machine learning by developing and transitioning capabilities to government sponsors.

Your day-to-day research tasks will include:

  • Identifying and investigating emerging AI and AI-adjacent technologies.
  • Performing and publishing impactful original research in the field of AI and ML algorithm vulnerabilities and securing against those vulnerabilities.
  • Adapting and applying existing research in the field to solve real-world problems.
  • Transitioning and providing guidance on AI capabilities to government sponsors.

Duties:

  • Hands-on research: You'll conduct and lead novel research in applied machine learning and artificial intelligence.
  • Solution development: You'll work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.
  • Strategy: You'll work with the leadership team and colleagues to plan, develop, and carry out an overall research strategy, and to influence the national research agenda regarding future technology.
  • Collaboration: You'll actively participate on teams of software developers, researchers, designers, and technical leads. You'll build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research directions.
  • Mentoring: You'll contribute to improving the overall technical capabilities of the Division by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI AI Division.

Knowledge and Experience:

  • Comprehensive knowledge of machine learning; previous experience in adversarial machine learning preferred but not required
  • A track record of conducting research and applying scientific methods to solve difficult problems
  • Experience leading research projects in novel areas with limited previous work to build upon
  • Ability to work with leadership to plan, develop, and deliver an overall research strategy
  • Strong written and verbal communication skills; ability to convey complex technical ideas in a layperson's terms
  • Proficiency in writing funding proposals or pitching ideas for new research projects
  • Ample experience with publishing written or technical artifacts showcasing your work
  • Strong collaboration skills for working with colleagues and sponsors
  • Willingness to guide and mentor junior team members

Requirements:

  • A bachelor's degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD with five (5) years of experience
  • Willingness to work onsite at an SEI facility 5 days per week.
  • Be able to obtain and maintain an active Department of War security clearance.
  • Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences.

Location: Arlington, VA, Pittsburgh, PA

Job Function: Software/Applications Development/Engineering

Position Type: Staff – Regular

Full time/Part time: Full time

Pay Basis: Salary

More Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance