Signify Netherlands B.V.
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Bengaluru · On-site · 1-3 Yrs · Oct 17
Consumer Product Manufacturing · 10000+ Employees · Eindhoven, Netherlands
Signify is the world leader in lighting. We provide professional customers and consumers with quality products, systems, and services. Our connected lighting offerings bring light and the data they collect to devices, places, and people - redefining what light can do and how people use it. We are a global company, present in more than 70+ countries, with 90+ nationalities represented at Signify. Working for Signify means being creative and adaptive. Our culture of continuous learning and commitment to diversity, equity, and inclusion creates an environment that allows you to build your skills and career.
Hiring: Engineering
What employees say
+ Work-life balance Career growth Strong technology ecosystem
− None. All good. No Cons
More reviews on the company profile.
Interview experience · Intern
Good professional i got selected from college i have clear 2 round aptitude questions and coding where the conducted technical round where problem and python code are asked the the technical interview
Average difficulty · India · 107 reports
More interview insightsJob description
Overview
Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting.
Responsibilities
- Contribute to the design and implementation of scalable ML infrastructure supporting model training, deployment, and inference.
- Develop and deploy ML solutions as modular, reusable microservices using APIs, enabling flexible integration with enterprise applications.
- Package ML models and services using Docker and deploy them using orchestration platforms such as Kubernetes to ensure scalability, portability, and reliability.
- Monitor production systems for model performance, latency, and drift; support optimization and improvements.
- Build and maintain CI/CD pipelines for ML workflows, including versioning, testing, and automated deployment.
- Develop and maintain scalable data pipelines for batch and real-time processing to support model training and inference.
- Contribute to the development of multi-agent or agent-based solutions (e.g., orchestration of LLM agents, task-specific services, or workflow agents) to solve complex business problems.
- Troubleshoot issues across distributed ML systems and microservices; ensure system stability and uptime.
- Follow best practices for secure deployment, API management, and data privacy across distributed systems.
- Work with engineering, data science, and business teams to deliver scalable, production-ready solutions.
- Stay updated on emerging technologies in ML, MLOps, distributed systems, and AI (including GenAI and agent-based frameworks).
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- Strong understanding of machine learning algorithms, statistical modeling, and applied data science use cases.
- Experience with ML lifecycle management and tools such as AWS SageMaker, Azure ML, Dataiku, or similar platforms.
- Hands-on experience building RESTful APIs and deploying ML models as microservices using frameworks such as FastAPI, Flask, or similar.
- Working knowledge of Docker for containerization and Kubernetes for service orchestration, scaling, and deployment.
- Exposure to designing or integrating multi-agent systems, LLM-based agents, or distributed service-based architectures is a strong plus.
- Experience with data processing frameworks such as Spark, Hadoop, or NoSQL databases.
- Hands-on experience with AWS or Azure, including deploying and managing scalable ML solutions.
- Proficiency in Python and SQL; familiarity with Java/Scala is a plus.
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Job application FAQ
Last updated 27 October 2026
- How do I apply for ML Operations Engineer at Signify Netherlands B.V.?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Signify Netherlands B.V. may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this ML Operations Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is ML Operations Engineer remote or on-site in Bengaluru, Karnataka?
- This listing is marked on_site with location Bengaluru, Karnataka. Confirm details on the job description before applying.
- What skills matter for this ML Operations Engineer role at Signify Netherlands B.V.?
- This is a mid-level ML Operations Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.