Lead ML Operations Engineer

Job TitleLead ML Operations Engineer

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. You light the way. ​

More about the role​

• As the MLOps Lead, you’ll spearhead the development of robust, scalable machine learning infrastructure, playing a key role in deploying and optimizing ML models for regression, classification, and clustering.
• Leveraging AWS services such as SageMaker, EC2, Lambda, CloudWatch, S3, RDS, Load Balancer, API Gateway, and Container Registry, along with Snowflake for advanced data management, you’ll build automated ML pipelines that drive business insights. You will also handle streaming data and manage streaming ML tasks, ensuring real-time data processing and insights. SQL is essential for optimizing the management and querying of large datasets, facilitating efficient data integration and retrieval across the platform.
• You’ll develop APIs using FastAPI and Flask, as well as Streamlit apps for delivering interactive analytics solutions to stakeholders.
• Your expertise in Docker and Kubernetes will ensure model scalability and resilience. Utilizing collaboration tools like Git, Jira, and Confluence, you’ll maintain seamless workflows and drive efficient project management.
• Additionally, your experience with Azure AD will enhance security and identity management within our cloud infrastructure. Your role will be critical in delivering data-driven decisions that propel the company forward. ​

More about you

• You’re a highly skilled professional with 7+ years of experience in MLOps or DevOps, specializing in deploying models at scale, including statistical models, deep learning models, and language models.
• You have hands-on experience in streaming data and are adept at handling streaming ML tasks, ensuring real-time data processing and insights.
• SQL is one of your core strengths, enabling you to work with large datasets and optimize queries for efficient data processing in platforms like Snowflake.
• You’re proficient with AWS services including SageMaker, Lambda, EC2, CloudWatch, S3, RDS, Load Balancer, API Gateway, and Container Registry, and have expertise in containerization (Docker, Kubernetes) and API development using FastAPI and Flask. Additionally, your experience with Streamlit will allow you to create engaging analytics solutions that provide actionable insights.
• Your experience in managing team collaboration through Git, Jira, and Confluence, along with your ability to enforce code quality with Pylint and other linters, ensures smooth workflows. You thrive in fast-paced environments, deploying Generative AI models and managing the full ML lifecycle, while your technical and problem-solving skills set you apart as an innovative leader.

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 30,000+ people.

We believe that a diverse and inclusive workplace fosters creativity, innovation, and a full spectrum of bright ideas. With a global workforce representing 99 nationalities, we are dedicated to creating an inclusive environment where every voice is heard and valued, helping us all achieve more together.