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Mathematical Optimization Jobs (NOW HIRING)

FEDRUS GLOBAL LLC

Senior Applied Scientis

Irvine, CA · On-site

Hands-on mathematical optimization for regional store allocation Extend existing constraint-based, multi-objective allocation framework to new regional store configurations Adapt models to regional ...

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How much do mathematical optimization jobs pay per year?

As of Aug 27, 2026, the average yearly pay for mathematical optimization in the United States is $55,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $72,500.00 per year, depending on experience, location, and employer.

What is a mathematical optimization?

A Mathematical Optimization job involves using mathematical techniques and algorithms to find the best possible solution to a given problem while satisfying constraints. Professionals in this field work in industries like finance, logistics, engineering, and artificial intelligence to optimize processes, minimize costs, or maximize efficiency. They use tools like linear programming, integer programming, and machine learning to solve complex decision-making problems.

What do mathematical optimization professionals do?

Professionals in Mathematical Optimization often work on projects involving resource allocation, supply chain management, scheduling, logistics, network design, or financial portfolio optimization. They use mathematical models to define and solve problems where the objective is to maximize efficiency or minimize costs under various constraints. Work may include collaborating with cross-functional teams to gather requirements, analyze large datasets, develop optimization algorithms, and implement solutions within existing business systems. These roles are found across industries such as manufacturing, transportation, finance, and technology, providing diverse and challenging opportunities. This variety in project scope allows for continuous learning and professional growth.

What are the key skills and qualifications needed to thrive in mathematical optimization?

To thrive in Mathematical Optimization, you need a strong background in mathematics, statistical modeling, and algorithm development, often supported by a degree in mathematics, operations research, engineering, or related fields. Proficiency with programming languages such as Python, MATLAB, or specialized optimization software (like Gurobi, CPLEX, or AMPL) is typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate complex concepts clearly are critical soft skills for this role. These skills enable professionals to design effective solutions, interpret results, and convey recommendations to both technical and non-technical stakeholders.

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Mathematical Optimization jobs near you
Infographic showing various Mathematical Optimization job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 78% Physical, 5% Hybrid, and 17% Remote job distribution, with an average salary of $55,794 per year, or $26.8 per hour.

Senior Engineer, Quantum Algorithms (Optimization)

QUANTUM COMPUTING, INC.

Hoboken, NJ

Full-time

Re-posted 5 days ago

Job description

Job Title: Software Engineer, Quantum Algorithms (Optimization) 

Location: Hoboken, NJ

Division: Technology 

Department: Engineering 


About Us

Quantum Computing Inc. (QCi) (Nasdaq: QUBT) is an innovative, integrated photonics company that provides accessible and affordable quantum machines to the world today. QCi products are designed to operate at room temperature and low power at an affordable cost. The Company’s portfolio of core technology and products offer unique capabilities in the areas of high-performance computing, artificial intelligence, cyber security as well as remote sensing applications.

Position Description 

We are looking for a Software Engineer with deep expertise in Mathematical Optimization and quantum algorithm development. This role is critical in architecting the core software engine that drives our proprietary photonic quantum processors, combining complex mathematical formulations with physical optical hardware feedback.

Responsibilities

  • Design and implement the high-performance C++ runtime and Hardware Abstraction Layer (HAL) for photonic optimization computers
  • Profile and optimize critical execution paths to minimize latency, addressing bottlenecks in memory bandwidth, cache locality, and data transfer
  • Collaborate with FPGA, Electrical engineers and Firmware engineers to ensure to create, test, and optimize device interfaces.
  • Develop algorithmic enhancements to usage of quantum feedback to solve NP hard optimization problems more efficiently with higher solution quality.
  • Write efficient, thread-safe code for concurrent hardware control and real-time signal processing.
  • Design and implement novel algorithms that map optimization and machine-learning problems onto entropy-based photonic quantum processors, including post-processing pipelines.
  • Build software layers to decompose and orchestrate large-scale optimization problems across multiple photonic hardware resources.
  • Contribute to quantum algorithms on the company roadmap

Required Qualifications

  • 6+ years of experience in software engineering with a focus on systems or HPC.
  • Strong proficiency in C++ and Python
  • Experience with quantum algorithms, quantum information, or quantum optics.
  • Strong mathematical background in Convex Optimization, Quadratic Programming (QP), Mixed-Integer Linear Programming (MILP), or Gradient-Free Methods.
  • Experience with  Numerical Analysis and high-performance math libraries (e.g., BLAS, LAPACK, Eigen).
  • Familiarity with protocols (e.g., UART, SPI, gRPC, REST) and software integration.
  • Strong understanding of performance tuning, memory management, and fault-tolerant design.
  • Familiarity with Linux system programming and build toolchains (CMake, GCC/Clang).
  • Experience working in cross-functional teams involving hardware, physics, and software.

Preferred Qualifications

  • Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics.
  • Experience with classical optimization solvers (e.g., CPLEX, Gurobi) or heuristic frameworks.
  • Familiarity with Open Quantum Systems or optical feedback mechanisms.
  • Background in Digital Signal Processing (DSP) or control theory.
  • Knowledge of containerized deployment using Docker.

Skills 

C++, Quantum Algorithms, High Performance Computing (HPC), Algorithm Design, Mathematical Optimization,, Multi-threading, Linux, CMake, Python, Performance Profiling, Hardware Abstraction, Signal Processing

Quantum Computing Inc. (QCi) is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.

Incumbent(s) in this position may be required to perform other duties and special assignments not specifically stated above. Statements outlined in this section are designated as essential job functions in accordance with the Americans with Disabilities Act of 1990.