ML Operations Engineer

Philips Lighting Spain SL.; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Signify is seeking a highly skilled ML Engineer to build and support scalable ML and MLOps systems. You will work with data scientists and engineers to operationalize models, deploy as microservices, and integrate intelligent components into production workflows.

You will design scalable ML pipelines, containerize with Docker, orchestrate with Kubernetes, and contribute to multi-agent solutions. Strong Python/SQL skills and cloud experience are essential, with knowledge of Spark/Hadoop a plus.

Qualifications

• 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.

Responsibilities

• Contribute to design and implementation of scalable ML infrastructure supporting training, deployment, and inference.
• Develop and deploy ML solutions as modular, reusable microservices using APIs.
• Package ML models and services using Docker and deploy with Kubernetes for scalability and portability.
• Monitor production systems for model performance, latency, and drift; optimize accordingly.
• 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 training and inference.
• Contribute to multi-agent or agent-based solutions to solve complex business problems.
• Troubleshoot issues across distributed ML systems and microservices; ensure system stability.
• 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.

Skills

Machine Learning

ML lifecycle management

RESTful APIs

Docker

Kubernetes

Multi-agent systems

Big data

Cloud platforms

Python

SQL

Java/Scala

Education

Bachelor’s or Master’s in Computer Science or Data Science

Tools

FastAPI

Flask

AWS SageMaker

Azure ML

Dataiku

Job description

About Signify

Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting. Through our leadership in connected lighting and the Internet of Things, we’re breaking new ground in data analytics, AI, and smart solutions for homes, offices, cities, and beyond. At Signify, you can shape tomorrow by building on our incredible 125+ year legacy while working toward even bolder sustainability goals. Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers you to grow your skills and career. Join us, and together, we’ll transform our industry, making a lasting difference for brighter lives and a better world. More about the role

Job Summary

Builds and supports scalable Machine Learning (ML) and MLOps systems, enabling reliable model deployment through modern architectures such as microservices and containerized environments. Works closely with data scientists and engineers to operationalize models, improve performance, and integrate intelligent components including multi-agent systems into production workflows.

Key Areas of Responsibility

• 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).

Critical Experiences

• 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.

Everything we’ll do for you

You can grow a lasting career here. We’ll encourage you, support you, and challenge you. We’ll help you learn and progress in a way that’s right for you, with coaching and mentoring along the way. We’ll listen to you too, because we see and value every one of our 27,000+ people. We believe that a diverse and inclusive workplace fosters creativity, innovation, and a full spectrum of bright ideas. With a global workforce present in 70+ countries, we are dedicated to creating an inclusive environment where every voice is heard and valued, helping us all achieve more together. Come join us, and together we can light up the future. We are Signify, the new company name of Philips Lighting, and we light up the world! Our purpose is to unlock the extraordinary potential of light for brighter lives and a better world. We’re committed to the continuous development of our employees, using our learning to shape the future of light and create a sustainable future. Join the undisputed leader in the lighting industry and be part of our diverse global team.

#WeAreSignify #SignifyLife

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Signify is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex (including pregnancy), sexual orientation, gender identity, national origin, genetic information, creed, citizenship, disability, protected veteran or marital status. As an equal opportunity employer, Signify is committed to a diverse workforce. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants that require accommodation in the job application process may contact 888-367-7223, option 5, for assistance.

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Signify North America Corporation (“Signify”) will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential