Senior Software Engineer – Algorithm & ML Development
Thermo Fisher Scientific22 hours ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Design, implement, maintain, validate, and optimize algorithms for scientific and operational data.
- Develop production-quality Python workflows and reusable components for data analysis, mathematical modeling, predictive analytics, signal processing, image processing, and machine learning.
- Analyze complex datasets, derive features, and create predictive or diagnostic insights.
- Evaluate algorithm performance through testing, benchmarking, validation, and defined performance criteria.
- Adapt and migrate analytical and algorithmic workloads from AWS to Databricks, Spark/PySpark, Delta-based datasets, and distributed compute.
- Develop reusable feature-generation logic for experimentation, model training, batch inference, and production applications.
- Contribute to ML lifecycle practices including experiment tracking, reproducibility, model validation, versioning, deployment, monitoring, and retraining.
- Collaborate with data engineers, data scientists, platform engineers, domain experts, and application teams to productionize algorithms and models.
- Apply source control, automated testing, code review, CI/CD, documentation, and observability practices.
- Participate in technical design, solution reviews, estimation, and implementation planning.
- Mentor less experienced engineers and contribute to engineering standards and reusable development practices.
Requirements
- 8–12 years of professional experience in software engineering, algorithm development, scientific computing, data science, machine learning, or related technical disciplines.
- Strong hands-on Python programming experience and experience developing production-quality Python software.
- Experience with scientific computing and data analysis libraries such as NumPy, pandas, and SciPy.
- Experience designing and implementing data-processing, analytical, mathematical, or predictive algorithms.
- Experience with complex datasets, data-driven models, features, or analytical workflows.
- Experience in areas such as machine learning, predictive analytics, signal processing, image processing, time-series analysis, optimization, or statistical modeling.
- Understanding of machine learning fundamentals including feature engineering, model training, validation, evaluation, and inference.
- Experience converting exploratory or prototype algorithms into maintainable production implementations.
- Understanding of modular design, object-oriented programming, testing, maintainability, and performance optimization.
- Experience with cloud-based data and compute environments, preferably AWS.
- Working knowledge of SQL and structured datasets.
- Understanding of scalable and distributed data-processing concepts.
- Experience with source control systems such as Git.
- Understanding of CI/CD, automated testing, DevOps practices, and modern software development workflows.
- Preferred experience includes Apache Spark or PySpark, Databricks, Delta Lake, MLflow, feature stores, Unity Catalog, production ML inference, MLOps, Docker, and workload optimization.
- 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.