Campus Pride Jobs

Company Description

When you’re one of us, you get to run with the best. For decades, we’ve been helping marketers from the world’s top brands personalize experiences for millions of people with our cutting-edge technology, solutions and services. Epsilon’s best-in-class identity gives brands a clear, privacy-safe view of their customers, which they can use across our suite of digital media, messaging and loyalty solutions. We process 400+ billion consumer actions each day and hold many patents of proprietary technology, including real-time modeling languages and consumer privacy advancements. Thanks to the work of every employee, Epsilon India is now Great Place to Work-Certified™. Epsilon has also been consistently recognized as industry-leading by Forrester, Adweek and the MRC. Positioned at the core of Publicis Groupe, Epsilon is a global company with more than 8,000 employees around the world. For more information, visit epsilon.com/apac or our LinkedIn page.

Overview

As an AIOps Engineer, you will lead the design and development of AI solutions to improve system reliability and resilience. Your focus will be on building automation to reduce manual effort and prevent incidents, particularly in incident management. You'll need expertise in AI technologies, strong problem-solving abilities, and a background in software development & understanding of Operations. Collaborating with cross-functional teams, you'll implement scalable and robust AIOps solutions, helping customers to separate signal from noise across billions of data points and providing AI-based root cause analysis. JOB RESPONSIBILITIES: Assist in design and deployment of AI/ML solutions, ensuring alignment with business goals and technical requirements. Collaborate with service and solution owners, technical & application teams to gather requirements, identify use cases, and propose solutions. Integrations with monitoring tools for metrics, logs and traces across infra, app, security, network domains Integration with tools such as AppDynamics, New Relic, Splunk, Azure Log Analytics, ServiceNow and RunDeck etc. Implement scalable, efficient, and robust AI models, algorithms, and systems. Collaborate with service and solution owners, technical, and non-technical teams to collect, clean, and prepare data for AI model training and evaluation. Develop and maintain best practices and coding standards for AI solution development. Troubleshoot and resolve technical issues related to AI systems. Create content (Docs, workflow diagrams, testing plans, training) related to specific use cases or best practices. Monitor AIOps dashboards for Continual Improvement Opportunities. Stay up-to-date on advancements in AI technologies and research to drive innovation and continuous improvement. Design, implement, and maintain AIOps solutions to monitor and analyze IT systems, applications, and networks. Deploy machine learning algorithms for anomaly detection, root cause analysis, and incident prediction. Conduct root cause analysis for incidents using data from AIOps and observability tools to identify underlying issues. Continuously analyze monitoring data to identify trends, anomalies, and opportunities for optimization. Stay updated with industry trends and advancements in AIOps and observability practices, and recommend new tools or methodologies for adoption Designing, developing, and implementing AI models and algorithms utilizing state-of-the-art techniques. Collaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals. Conducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services. Optimizing existing generative AI models for improved performance, scalability, and efficiency. Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation. Developing clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders. Contributing to the establishment of best practices and standards for generative AI development within the organization. Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines Implement monitoring and logging tools to ensure AI model performance and reliability Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.

Qualifications

Minimum 4 years of experience in Data Science and Machine Learning Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field. 8+ years of industry experience in software development. Strong proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch Hands-on experience in Java, Spring Boot, REST Web Services, Kafka, and Microservices architecture. Experience with AIOps and machine learning is highly desirable. Knowledge of OpenTelemetry is an added advantage. Experience with other monitoring tools like Prometheus, Grafana, etc. In-depth knowledge of machine learning, deep learning, and generative AI techniques Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models Experience with cloud platforms such as Azure or AWS Expertise in data engineering, including data curation, cleaning, and preprocessing Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Track record of driving innovation and staying updated with the latest AI research and advancements Knowledge of IT operations concepts and processes, such as monitoring, incident management, root cause analysis, remediation. You have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques. You have strong knowledge of data structures, algorithms, and software engineering principles.

Additional Information

Epsilon is a global data, technology and services company that powers the marketing and advertising ecosystem. For decades, we’ve provided marketers from the world’s leading brands the data, technology and services they need to engage consumers with 1 View, 1 Vision and 1 Voice. 1 View of their universe of potential buyers. 1 Vision for engaging each individual. And 1 Voice to harmonize engagement across paid, owned and earned channels.

Epsilon’s comprehensive portfolio of capabilities across our suite of digital media, messaging and loyalty solutions bridge the divide between marketing and advertising technology. We process 400+ billion consumer actions each day using advanced AI and hold many patents of proprietary technology, including real-time modeling languages and consumer privacy advancements. Thanks to the work of every employee, Epsilon has been consistently recognized as industry-leading by Forrester, Adweek and the MRC. Epsilon is a global company with more than 9,000 employees around the world.

Epsilon has a core set of 5 values that define our culture and guide us to create value for our clients, our people and consumers. We are seeking candidates that align with our company values, demonstrate them and make them meaningful in their day-to-day work:

· Act with integrity. We are transparent and have the courage to do the right thing.

· Work together to win together. We believe collaboration is the catalyst that unlocks our full potential.

· Innovate with purpose. We shape the market with big ideas that drive big outcomes.

· Respect all voices. We embrace differences and foster a culture of connection and belonging.

· Empower with accountability. We trust each other to own and deliver on common goals.