Algorithm Engineer

Key Responsibilities

• Design, develop, test, and optimize algorithms for mass spectrometry data analysis, including feature finding, signal processing, peak detection, data extraction, pattern recognition, and related analytical workflows.
• Enhance and maintain existing algorithms used across Agilent software applications to improve accuracy, performance, scalability, usability, and reliability.
• Apply machine learning, statistical modeling, numerical methods, signal processing, and data structures/algorithms to solve complex scientific data analysis problems.
• Develop production-quality analytical software components that support biochemical analysis of mass spectrometry data across multiple applications and customer workflows.
• Partner with software engineers to implement algorithms within Agilent software platforms, with a focus on maintainable, testable, and scalable code.
• Collaborate with internal scientists, application experts, and external customers to understand algorithm, data analysis, and visualization needs.
• Invent, prototype, and re-engineer software algorithms and data analysis approaches that improve how users interpret complex scientific data sets.
• Participate in engineering discussions, design reviews, and technical problem-solving sessions with cross-functional teams.
• Design and execute validation strategies, test plans, benchmarks, and performance analyses to ensure algorithms meet functional, scientific, and performance requirements.
• Support modernization efforts by contributing to algorithm and software architecture improvements across current and future Agilent data analysis platforms.
• Use modern development practices and AI-enabled tools, where appropriate, to improve development efficiency, analysis capability, and engineering productivity.
• Communicate technical concepts clearly to engineering partners, scientists, stakeholders, and customers.

Required Qualifications

• Master’s or Ph.D. degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, Electrical Engineering, Bioinformatics, Analytical Chemistry, or a related technical/scientific field.
• 4+ years of experience developing production-grade algorithms, analytical software, scientific software, or data analysis tools.
• Strong programming skills in C#, C++, Python, Java, or similar programming languages, with willingness to work in a Microsoft/C# development environment.
• Strong foundation in scientific algorithm development, with expertise in one or more of the following: signal processing, numerical methods, statistical modeling, machine learning, pattern recognition, optimization, or computational science.
• Experience working with complex numerical or scientific data sets and developing methods to identify patterns, extract meaningful signals, and improve analytical interpretation.
• Ability to write clean, maintainable, testable code and collaborate effectively within an engineering development environment.
• Strong problem-solving skills, curiosity, and ability to work through ambiguous scientific and technical challenges.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience with mass spectrometry, LC/MS, GC/MS, chromatography, proteomics, biopharma workflows, large molecule characterization, small molecule analysis, food safety, environmental testing, or related analytical science domains.
• Experience developing algorithms for feature detection, peak identification, signal processing, quantitative analysis, visualization, chemometrics, or scientific workflow automation.
• Familiarity with AI-enabled development tools, agent-based tools, or applied machine learning approaches for scientific data analysis or software development.
• Experience working with scientists, application specialists, customers, or cross-functional product development teams.
• Background in bioinformatics, computational chemistry, analytical chemistry, life sciences, or scientific instrumentation software.
• Experience contributing to commercial software products, regulated scientific software, or software used in laboratory environments.