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Algorithm Engineer Jobs in Pittsburgh, PA (NOW HIRING)

Solomon Page

Software Engineer

Pittsburgh, PA · On-site

$200K - $400K/yr

They seek a Software Engineer specializing in C++ to build high-performance systems for sensor ... Optimize algorithms for low-latency performance and high reliability in production environments

Compunnel

Software Engineer

Pittsburgh, PA · On-site

... algorithms, operating systems, and distributed systems concepts to software development activities. • Support DevOps initiatives including CI/CD pipelines, automation, and testing practices. • ...

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All JobsAlgorithm Engineer JobsAlgorithm Engineer Jobs in Pittsburgh, PA

Algorithm Engineer information

See Pittsburgh, PA salary details

$55.6K

$104.3K

$189.7K

How much do algorithm engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for algorithm engineer in Pittsburgh, PA is $104,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,200.00 and $123,800.00 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.
What are popular job titles related to Algorithm Engineer jobs in Pittsburgh, PA? For Algorithm Engineer jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Algorithm Engineer jobs in Pittsburgh, PA look for? The top searched job categories for Algorithm Engineer jobs in Pittsburgh, PA are:
What cities near Pittsburgh, PA are hiring for Algorithm Engineer jobs? Cities near Pittsburgh, PA with the most Algorithm Engineer job openings:
Algorithm Engineer jobs near you
R&D Software Engineer -- AI/ML Mission Solutions

R&D Software Engineer -- AI/ML Mission Solutions

Rackner

Pittsburgh, PA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 days ago

Job description

R&D Software Engineer — AI/ML Mission Solutions

Location: United States
Work Model: Remote
Travel: Approximately 15% for R&D events, technical demos, and collaboration sessions
Clearance: U.S. citizenship required. Active Secret clearance preferred; candidates must be eligible to obtain and maintain a U.S. government security clearance.

Build AI/Data Capabilities for Mission-Focused R&D

Rackner is hiring an R&D Software Engineer — AI/ML Mission Solutions to help build, prototype, validate, and improve AI/data-driven software capabilities for defense-relevant use cases.

This is a hands-on R&D role for an engineer who enjoys solving hard problems across software, data, AI/ML, algorithms, RAG, agentic systems, simulation, or pipeline workflows. You will work with Rackner's internal R&D team to turn ambiguous ideas, operational needs, and user feedback into working technical capabilities.

We are not looking for one person to be an expert in every area. The strongest candidates bring one deep technical lane — such as AI/ML systems, RAG/agentic workflows, data pipelines, Python/Go development, Kubernetes/deployable systems, MLOps, or algorithmic software — plus enough working knowledge in adjacent areas to contribute in a fast-moving R&D environment.

This is not a traditional sales role and not a platform-only engineering role. Kubernetes, Terraform, cloud, CI/CD, and DevSecOps are helpful, but the main focus is software engineering, AI/data systems, algorithmic problem-solving, validation, and R&D execution.

What You'll Do

  • Design, prototype, test, and refine AI/data-driven software capabilities for mission-focused use cases
  • Build software for AI/ML experimentation, RAG or agentic workflows, model integration, simulation, data pipelines, and applied R&D prototypes
  • Develop and improve data workflows, schema transformations, JSON workflows, APIs, backend services, and integration layers
  • Support AI/ML workflows including inference, evaluation, deployment, monitoring, and model-serving patterns
  • Validate outputs through testing, data quality checks, evaluation methods, debugging, monitoring, and failure analysis
  • Troubleshoot complex issues across software, data, model, and integration layers
  • Work with engineers and technical leadership to assess tradeoffs, identify constraints, and improve solution design
  • Participate in technical demos, R&D events, mission-user discussions, and feedback cycles as needed
  • Convert stakeholder or mission feedback into actionable technical steps
  • Clearly explain technical concepts to engineering teams, program stakeholders, customers, and mission users

What You'll Bring

  • Strong software engineering background with hands-on experience building, testing, debugging, and improving modern systems
  • Proficiency in Python, Go, C++, Java, SQL, or a similar language used for backend, data, AI/ML, or algorithmic work
  • Hands-on depth in at least one relevant area: AI/ML systems, RAG, agentic development, LangChain, data pipelines, MLOps, algorithmic software, simulation, or deployable systems
  • Ability to clearly explain what you personally built, how the system worked, what broke, how you validated it, and what impact it had
  • Familiarity with real-world data workflows, including data sources, APIs, schemas, transformations, databases, files, events, or logs
  • Comfort working in fast-paced environments with evolving requirements
  • Willingness to travel approximately 15% for R&D events, demos, collaboration sessions, or customer and mission engagements

Experience That Stands Out

  • DoD, Air Force, Platform One, Big Bang, mission planning, C2, ISR, autonomy, or defense technology experience
  • AI/ML systems, applied AI workflows, RAG, agentic development, LangChain, model integration, evaluation, deployment, serving, registry, or monitoring
  • MLOps tools or workflows such as MLflow, SageMaker, Databricks, Kubeflow, Airflow, Dagster, Prefect, or similar tools
  • Data pipelines, ETL/ELT workflows, schema transformations, JSON transformations, dbt pipelines, or messy data integration workflows
  • Data validation, data quality checks, pipeline monitoring, failure handling, debugging, or observability for data/model workflows
  • Algorithms, optimization, simulation, scientific computing, applied mathematics, physics-informed software, computer vision, autonomy, or robotics
  • Python, Go, C++, SQL, PyTorch, TensorFlow, scikit-learn, FastAPI, Postgres, or related software/data/AI tooling
  • Technical demos, pilots, field exercises, workshops, briefings, or customer / mission-user discussions
  • Cloud, Docker, Kubernetes, Terraform, CI/CD, DevSecOps, ATO, or secure delivery experience

About Rackner

Rackner is a software consultancy focused on building mission-critical systems for the U.S. government. Our teams work across cloud platforms, DevSecOps, AI/ML, distributed systems, and modern software engineering initiatives supporting federal agencies and national security missions.

Rackner engineers and technical teams collaborate closely with leadership, program teams, and mission stakeholders to design, demonstrate, and improve software systems that address complex operational challenges.

Benefits & Perks

Rackner invests in its people, because when you grow, we all win.

  • Company-supported certifications aligned to current and future program work, including cloud, Kubernetes, DevSecOps, security, AI/ML, project management, and related technical areas
  • Clear advancement tracks and future leadership opportunities
  • 401(k) with 100% match up to 6%
  • Comprehensive medical, dental, vision, life, and disability coverage
  • Generous PTO and paid holidays
  • Home-office equipment plan and remote work support
  • Fitness and wellness reimbursement
  • Weekly pay schedule and modern perks, including team events

Equal Opportunity

Rackner is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.