Principal ML Engineer

Working for Signify means being creative and adaptive while working in a fast-paced company. Our culture of continuous learning and commitment to diversity and inclusion creates an environment that allows you to build your skills and career while transforming our industry.

As the world leader in lighting, we’re constantly ahead of the curve. Through our leadership in connected lighting and the Internet of Things, we’re breaking new grounds in data analytics, AI, and smart homes, offices, cities and more!

Signify is one of the few companies in the world to achieve carbon neutrality and our next sustainability goals are even bolder: doubling our positive impact on the environment and society by 2025.

We’re on the lookout for forward-thinking innovators with a passion for sustainability. If you match this description, get in touch!

We’re looking for a MLOps Lead to translate business needs into actionable technical requirements for analytics projects requiring periodic updates, ensuring these solutions meet quality, scalability, and replicability standards. Take responsibility for the overall technical performance, security, and smooth operation of assigned data products and productized analytics solutions; Manage on-time, on-budget refresh of existing analytics solutions to maintain their usability for business stakeholders. Identify and communicate risks and roadblocks effectively.

Collaboration with various stakeholders and analytics leads to ensure successful solution adoption.

Applicants will be expected to work with a diverse set of data sources, such as time series data, graph data, semi-structured and unstructured data, and maintain statistical/machine-learning models in support of on-demand, real-time analytic services. The applicant should also have strong skills in explaining the analytic solutions and outcomes to business stakeholders. You’ll be part of the Signify’s Enterprise Data & Analytics team, based in Bangalore.

What you’ll do

• Manage analytics solutions end to end by implementing best in class governance and compliance frameworks. Provide regular project updates, including risks and mitigation plans. Track projects in Jira using Agile methodology (if applicable). Coordinate with internal teams for project execution. Present analysis findings to stakeholders.
• Design and build a scalable infrastructure for deploying machine learning models. Develop and implement best practices for managing and monitoring machine learning workflows. Collaborate with data scientists and engineers to ensure smooth integration of machine learning models into production systems.
• Identify and implement new technologies and tools to improve the efficiency and effectiveness of machine learning operations. Continuously monitor and improve the performance of machine learning models in production.
• Knowledge Management: Create and maintain knowledge base articles (industry insights, case studies, code, lessons learned, etc.).
• Continuously learn and stay updated on the latest trends in advanced analytics. Collaborate with senior leaders to enhance own & team’s knowledge and expertise. Mentor a team of MLOps engineers. Stay up-to-date with the latest trends and advancements in data science, machine learning, and artificial intelligence
• Conduct data analysis, data mining, and data visualization to identify patterns and insights in large datasets
• Collaborate with cross-functional teams to develop and implement data-driven solutions that improve business performance
• Focus on productization & scalability of AI/ML solutions that can be replicated across multiple markets / businesses to solve similar business problems. Work with business groups to ensure models can be implemented as part of a delivered solution and can be replicated across multiple markets / countries
• Present findings to stakeholders to drive improvements and solutions from concept through to delivery

What you’ll need

• PhD / Masters / B.Tech in computer science, computer engineering with 12+ years of demonstrated experience in the MlOps / Machine Learning field
• Strong experience with at least one cloud computing platforms such as AWS, Azure, or GCP. Experience with containerization technologies such as Docker and Kubernetes. Strong understanding of machine learning concepts and techniques.
• Excellent communication and interpersonal skills, with the ability to work effectively in a team environment, and large scale solution management skills
• Demonstrated history of driving and delivering analytics solutions
• Strong problem-solving skills and the ability to think creatively and strategically. Ability and inclination to work in multi-disciplinary environments, and desire to see ideas realize in Practice.
• Knowledge of fundamentals of machine learning, data mining and statistical modeling, and working experience applying these methods to real world problems

What you’ll get in return…

• Opportunity to work on some of the highly complex and challenging business problems across a variety of functional domains and consumer markets.

• Competitive salary depending on experience.
• Extensive set of tools to drive your career, such as a personalized learning platform, free training and
• Coaching