Algorithm Engineer

Agilent is seeking an Algorithm Engineer to join our mass spectrometry data analysis software team in Santa Clara, CA. This role will focus on designing, developing, validating, and optimizing algorithms used to analyze complex scientific data generated by Agilent mass spectrometry systems and software platforms. 

The ideal candidate is someone who enjoys working deeply with data, identifying patterns, solving complex analytical problems, and translating scientific and customer needs into reliable, scalable software solutions. This role will support data analysis capabilities used across multiple applications, including workflows for biopharma, large molecule characterization, small molecule analysis, food safety, environmental analysis, and other life science and applied market applications. 

You will work closely with software engineers, test engineers, application scientists, internal scientific experts, and customer-facing teams to advance Agilent’s mass spectrometry data analysis capabilities. This is not a siloed role; the Algorithm Engineer will collaborate across teams to understand real scientific workflows, improve existing algorithms, and develop new approaches that help customers extract meaningful insights from complex data sets. 

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.