AI Engineering Expert

• Design, build, and deploy cutting-edge AI engineering platforms and components.
• Scale machine learning algorithms to process massive datasets efficiently.
• Develop and orchestrate model pipelines including feature engineering, inferencing, and continuous model training.
• Implement ML Ops practices for model KPI measurements, tracking, model drift & feedback loop.
• Collaborate with cross-functional teams to understand business needs and contribute in technical requirement gathering.
• Implement core features aligning with technical requirements.
• Write production-ready code that is easily testable, understandable by other developers, and accounts for edge cases and errors.
• Ensure high-quality deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews.
• Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths.
• Utilize bug tracking, code review, version control, and other tools to organize and deliver work effectively.
• Participate in agile ceremonies, and effectively communicate work progress, issues, and dependencies.
• Consistently contribute in researching & evaluating latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts, and creating prototype solutions.

• A bachelor's or master's degree in Computer Science or related field from a reputable university.
• 5+ years hands-on experience in ML development.
• Good fundamentals of machine learning.
• Strong programming expertise in Python, PySpark/Scala.
• Expertise in crafting ML models for high performance and scalability.
• Experience in implementing feature engineering, inferencing pipelines, and real-time model predictions.
• Experience in ML Ops to measure and track model performance, experience working with MLFlow.
• Experience with Spark or other distributed computing frameworks.
• Experience in ML platforms like Sage Maker, Kubeflow.
• Experience with pipeline orchestration tools such Airflow.
• Experience in deploying models to cloud services like AWS, Azure, GCP, Azure ML.
• Expertise in SQL, SQL DBs.
• Knowledgeable of core CS concepts such as common data structures and algorithms.
• Collaborate well with teams with different backgrounds / expertise / functions.

• Understanding of DevOps, CI/CD, data security, experience in designing on cloud platform;
• Experience in data engineering in Big Data systems

ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth, and professional development. Our robust skills development programs, multiple career progression options, internal mobility paths, and collaborative culture empower employees to thrive as individuals and global team members.

We are committed to giving our employees a flexible and connected way of working. A flexible ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel is a requirement at ZS for client-facing employees; business needs of your project and client are the priority. While some projects may be local, all client-facing employees should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.

Industry Type: Analytics / KPO / Research

Department: Engineering - Software & QA

Employment Type: Full Time, Permanent

Role Category: Software Development