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Software Engineer Applied Math Jobs in Massachusetts

hackerone

Software Engineer, Applied AI

Boston, MA

Software Engineer, Applied AI Location: Seattle, WA; Austin, TX; Boston, MA; Washington, DC 1 day onsite per week Position Summary At HackerOne, we're revolutionizing offensive security by combining ...

STR

Software Engineer

Woburn, MA · On-site

... Applied Mathematics, Electrical Engineering, or related field • Ability to obtain and maintain a ... software quality tools (static/dynamic analysis, automated testing frameworks) Company : STR is ...

hackerone

Senior Software Engineer, Applied AI

Boston, MA

$133.10K - $175.40K/yr

Senior Software Engineer, Applied AI Location: Seattle, WA; Austin, TX; Boston, MA; Washington, DC 1 day onsite per week Position Summary At HackerOne, we're revolutionizing offensive security by ...

STR

Senior Software Engineer

Woburn, MA · On-site

$130.80K - $172.40K/yr

They are seeking experienced Senior Software Engineers to join their cyber/networking team to ... Applied Mathematics, or a related field, with at least 5 years of relevant experience or equivalent ...

STR

Lead Software Engineer

Woburn, MA · On-site

STR is hiring experienced Lead Software Engineers to join their multidisciplinary cyber/networking ... Applied Mathematics, or a related field, with at least 7 years of relevant experience or equivalent ...

STR

Software Engineer

Woburn, MA

$111K - $140K/yr

... Applied Mathematics, Electrical Engineering, or related field * Ability to obtain and maintain a ... Experience with software quality tools (static/dynamic analysis, automated testing frameworks) Pay ...

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How much do software engineer applied math jobs pay per year?

As of May 30, 2026, the average yearly pay for software engineer applied math in Massachusetts is $161,114.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,100.00 and $188,900.00 per year, depending on experience, location, and employer.

What is a Software Engineer Applied Math job?

A Software Engineer in Applied Math develops and implements mathematical models, algorithms, and simulations to solve complex problems in various domains such as finance, engineering, and data science. They use programming languages like Python, C++, or MATLAB to create efficient solutions based on numerical analysis, optimization, and machine learning. This role often involves collaborating with scientists, analysts, and engineers to enhance computational methods and improve decision-making processes.

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

To thrive as a Software Engineer Applied Math, you need a solid background in computer science, mathematical modeling, and software engineering, often supported by a relevant degree such as computer science, applied mathematics, or engineering. Expertise in programming languages (such as Python, C++, or MATLAB), experience with numerical libraries and data analysis tools, and familiarity with version control systems are typically required. Strong analytical thinking, effective problem-solving, and the ability to communicate complex technical concepts are important soft skills for this role. These skills enable you to build efficient software solutions for complex mathematical problems, drive innovation, and collaborate effectively within technical teams.

What types of projects do Software Engineers in Applied Math typically work on?

Software Engineers specializing in Applied Math are often involved in developing algorithms, simulations, and analytical software that solve complex, real-world problems in fields like finance, engineering, machine learning, or data science. Daily responsibilities may include implementing mathematical models, optimizing existing code for performance, and collaborating with cross-disciplinary teams to refine solutions. Depending on the employer, you might work on projects such as risk modeling, signal processing, optimization engines, or predictive analytics tools. This role frequently requires balancing theoretical problem solving with practical software implementation to deliver robust, scalable applications. Working closely with researchers, data scientists, and other engineers, you will contribute to innovation and technical excellence in your organization's projects.
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Software Engineer Applied Math jobs near you

Senior Software Engineer, Applied AI

Lila Sciences

Cambridge, MA

$133.90K - $176.50K/yr

Other

Posted 2 days ago

Job description

Your Impact at LILA

We are seeking a Senior Software Engineer to join our Applied AI group and help build the next generation of our AI-driven scientific platform. In this role, you will design and optimize the backend systems, data pipelines, and AI integrations that power intelligent, data-driven applications. You'll work at the intersection of backend engineering and machine learning, ensuring our platform seamlessly scales and supports cutting-edge applied AI techniques such as Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration.

This role is ideal for someone who thrives in bridging software engineering and applied AI-turning research into production-grade systems that drive real-world scientific discovery. If you are passionate about building performant, elegant systems that make AI useful and impactful, we would love to hear from you!

What You'll Be Building

  • Applied AI Integration: Design and deploy backend services and data pipelines that directly support advanced AI applications, including LLMs, RAG, and agentic frameworks.
  • API & Service Development: Build high-performance APIs and microservices that enable seamless integration between AI models, scientific tools, and user-facing applications.
  • Data Pipeline Architecture: Architect and manage scalable pipelines capable of handling structured, unstructured, and vectorized data for AI/ML workloads.
  • Database & Knowledge Systems: Implement and optimize SQL, NoSQL, and vector databases to support low-latency AI retrieval and inference workloads.
  • Cloud & Infrastructure: Leverage AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to build robust, production-ready AI platforms.
  • Performance & Reliability: Diagnose system bottlenecks, optimize for cost and speed, and ensure the reliability and fault-tolerance of AI-driven workflows.
  • Collaboration: Partner with ML researchers, platform engineers, and scientists to translate models and algorithms into scalable, production-ready systems.

What You'll Need to Succeed

  • Educational Background: Bachelor's or Master's in Computer Science, Engineering, or a related field.
  • Backend & Data Expertise: 7+ years of professional experience building and scaling production systems, including APIs, data pipelines, and distributed services.
  • Programming Skills: Strong Python skills (FastAPI, Flask, Django), with solid experience in backend service development.
  • Databases: Proven experience with SQL, NoSQL, and vector databases; skilled in schema design, indexing, and query optimization.
  • Applied AI Systems: Hands-on experience integrating ML models or AI-driven workflows into production services.
  • Cloud & DevOps: Proficiency with AWS, Docker/Kubernetes, CI/CD pipelines, and infrastructure-as-code.
  • Communication & Problem-Solving: Ability to work cross-functionally with diverse teams and explain complex technical concepts to non-experts.

Bonus Points For

  • Scientific & Data-Intensive Domains: Experience working with life sciences, materials sciences, or other research-heavy fields.
  • Startup Experience: Comfort with fast-paced, iterative environments where impact and adaptability matter.

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