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Algorithm Engineer Jobs in Pennsylvania (NOW HIRING)

The Pennsylvania State University

Implement and test algorithms across multiple domains: underwater, terrestrial, aerial, and space ... Provide technical leadership on software engineering projects * Mentor team members in technical ...

The Pennsylvania State University

POSITION SPECIFICS We are seeking a Software Engineer to join our Applied Communications team of ... Implement and test algorithms across multiple domains: underwater, terrestrial, aerial, and space ...

Elutions

Domain Engineer

Philadelphia, PA · On-site

The Engineering Team is seeking a motivated, hard-working Domain Engineer with the ability to ... Understand big data concepts and have knowledge of data mining algorithms. * Read and understand ...

Elutions

Domain Engineer

Philadelphia, PA

The Engineering Team is seeking a motivated, hard-working Domain Engineer with the ability to ... Understand big data concepts and have knowledge of data mining algorithms. * Read and understand ...

Oxford Solutions

Robotics Engineer

Pittsburgh, PA · On-site

Oxford Solutions is working with a client to hire a Robotics Engineer for a direct hire, onsite ... Strong foundation in mathematics, algorithms, and advanced problem-solving * Experience with ...

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Algorithm Engineer information

See Pennsylvania salary details

$59.6K

$111.9K

$203.5K

How much do algorithm engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for algorithm engineer in Pennsylvania is $111,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,700.00 and $132,800.00 per year, depending on experience, location, and employer.

What are the typical challenges an Algorithm Engineer faces in their day-to-day work?

Algorithm Engineers often encounter complex problems that require creative, efficient solutions within strict performance or resource constraints. They may need to optimize existing algorithms, develop new ones from scratch, and ensure seamless integration into larger software systems, often while balancing accuracy, speed, and scalability. Collaborating with other engineers, data scientists, and product teams to align technical efforts with business goals is also a regular part of the job. Staying updated with the latest advancements in algorithms and technology is essential, making continuous learning a key aspect of the role.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, data engineering, and machine learning engineering can earn $500,000 or more annually, especially with experience, advanced skills, and stock options. These roles often require expertise in programming, algorithms, and sometimes leadership responsibilities in tech companies or startups.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and optimize AI models, but AI technology currently complements rather than replaces their role. MLEs are essential for building, deploying, and maintaining complex AI systems, and their expertise in data handling, model tuning, and system integration remains critical as AI advances. Continuous learning and familiarity with tools like TensorFlow or PyTorch are important for MLEs to stay relevant in evolving AI environments.

What does an algorithm engineer do?

An algorithm engineer designs, develops, and optimizes algorithms to solve complex problems and improve system performance. They often work with data structures, programming languages, and tools like Python or C++, and may test algorithms in simulation or real-world environments to ensure efficiency and accuracy.

What does an Algorithm Engineer do?

An Algorithm Engineer designs, develops, and optimizes algorithms to solve complex computational problems. They analyze data, improve system performance, and implement mathematical models for various applications, such as machine learning, computer vision, and optimization. This role requires proficiency in programming languages like Python or C++, strong mathematical skills, and an understanding of data structures and algorithms. Algorithm Engineers work closely with software developers, data scientists, and researchers to integrate efficient solutions into real-world systems.

What are the key skills and qualifications needed to thrive in the Algorithm Engineer position, and why are they important?

To thrive as an Algorithm Engineer, you need a strong background in mathematics, computer science, and programming, usually demonstrated with a degree in these fields and experience in algorithm design and analysis. Familiarity with languages like Python, C++, or Java, and tools such as MATLAB or TensorFlow, as well as relevant certifications like those in data science or machine learning, are typically advantageous. Outstanding problem-solving abilities, analytical thinking, and effective communication are critical soft skills for success in this role. These competencies are crucial because they enable Algorithm Engineers to design efficient, innovative solutions and collaborate seamlessly with multidisciplinary teams.

What engineers make $300,000 a year?

Senior engineers in high-demand fields such as software engineering, data engineering, and machine learning engineering can earn $300,000 or more annually, especially with extensive experience, advanced skills, and working at large tech companies or startups. Compensation often includes base salary, bonuses, and stock options, and requires strong technical expertise and certifications in relevant tools and programming languages.
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Algorithm Engineer jobs near you
Senior Machine Learning Engineer - Secure AI Lab

Senior Machine Learning Engineer - Secure AI Lab

Software Engineering Institute

Pittsburgh, PA • On-site

$111K - $152K/yr

Full-time

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

Job description

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.
Overview: As a Senior Machine Learning Engineer, you will specialize in engineering solutions that support 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.

As an engineer, you will solve problems for government sponsors by analyzing, designing, and building responsible AI systems.
Your day-to-day engineering tasks will include:
  • Identifying and investigating emerging AI and AI-adjacent technologies.

  • Defining and refining processes, practices, and tools for working with AI.

  • Designing and building well-engineered prototypes of AI systems.

  • Transitioning and providing guidance onAI capabilities to government sponsors.

Duties
  • Building Machine Learning Models and Systems: You will work with machine learning frameworks such as TensorFlow, PyTorch, Torch, and Caffe and modern programming languages including Python, C/C++, and Java. You will build and work with data pipelines, ETL processes, and backend systems. You will work with, extend, and implement state-of-the-art machine learning methods.

  • Technical Experimentation: You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision, natural language processing, planning and scheduling, robot control, and engineering safe, trusted, and reliable machine learning systems.

  • Testing and evaluation. You'll conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments. You'll evaluate systems for performance and security. You'll test capabilities using novel testing and analysis techniques.

  • Collaboration. You'll actively participate on teams of developers, researchers, designers, and technical leads. You'll collaborate with researchers and our government customers to understand challenges, needs, and possible solutions.

  • 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.

Knowledge and Experience
  • Comprehensive knowledge of machine learning; previous experience in adversarial machine learning desirable but not required

  • A track record of using well-established engineering practices to solve difficult problems

  • An understanding of how to convert research results into functioning prototypes or capabilities

  • Experience leading technical projects in novel areas with limited previous work to build upon

  • Strong written and verbal communication skills; able to convey complex technical ideas in a layperson's terms

  • 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 5 days per week at SEI offices in Pittsburgh, PA or Arlington, VA.

  • 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
SalaryMore 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

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