Software Engineer – Algorithm Development
Thermo Fisher Scientific23 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Develop and maintain algorithms for processing, analyzing, and modeling machine diagnostics and operational data.
- Build reusable Python-based computational workflows and analytical components using scientific-computing and data-analysis techniques.
- Develop algorithms for machine learning, predictive analytics, signal processing, image analysis, anomaly detection, time-series analysis, optimization, and statistical modeling.
- Test, validate, benchmark, and evaluate algorithm and model performance.
- Create reusable feature-generation logic and support model training, evaluation, inference, and productionization.
- Migrate and modernize analytical workloads from AWS to Databricks, including adaptation for Spark/PySpark, Delta-based datasets, and distributed computing.
- Apply ML lifecycle practices including experiment tracking, reproducibility, versioning, automated testing, deployment, and monitoring.
- Collaborate with software engineers, data engineers, data scientists, domain experts, and platform teams on technical solutions.
- Participate in code reviews, technical design discussions, estimation, testing, implementation planning, documentation, and observability efforts.
Requirements
- 5–8 years of professional experience in software engineering, algorithm development, scientific computing, data science, machine learning, or related technical disciplines.
- Strong Python programming skills and experience developing reliable, maintainable, modular, and testable software.
- Experience with scientific-computing and data-analysis libraries such as NumPy, pandas, and SciPy.
- Experience implementing data-processing, analytical, mathematical, predictive, or machine-learning algorithms.
- Experience working with complex datasets and developing data-driven models, features, or analytical workflows.
- Understanding of machine-learning fundamentals including feature engineering, model training, validation, evaluation, and inference.
- Experience converting exploratory or prototype code into structured, testable, maintainable implementations.
- Understanding of software-engineering fundamentals including modular design, object-oriented programming, testing, maintainability, and performance.
- Experience with cloud-based compute or data environments, preferably AWS.
- Working knowledge of SQL and structured datasets, plus a basic understanding of scalable or distributed data processing.
- Experience with source-control systems such as Git and familiarity with automated testing, CI/CD, Agile, DevOps, or modern software-development practices.
- Preferred experience includes Apache Spark or PySpark, Databricks, notebooks, managed compute, Delta Lake, MLflow, feature stores, model registries, Unity Catalog, batch or real-time inference, MLOps, Docker, and integration of algorithms into APIs or applications.
- Preferred domain experience includes scientific instrumentation, engineering data, image data, sensor data, or industrial R&D, scientific, engineering, or product environments.
- Bachelor’s or master’s degree in Computer Science, Data Science, Mathematics, Physics, Electronics, Engineering, or a related technical discipline.
Benefits
- Standard Monday–Friday work schedule.
- Office-based work environment.
Categories
About Thermo Fisher Scientific
Thermo Fisher Scientific builds analytical instruments, lab equipment and consumables, specialty diagnostics, and provides pharma services (CDMO and clinical research) for biotech, pharma, academic, and healthcare customers. It earns revenue through product sales, e-commerce distribution (Fisher Scientific), and contract services under brands such as Thermo Scientific, Applied Biosystems, Invitrogen, Patheon, and PPD. Headquartered in Waltham, MA, it is publicly traded on the NYSE (TMO) and was created by the 2006 merger of Thermo Electron and Fisher Scientific.