ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS.

What You’ll Do:

Build, Refine and Use ML Engineering platforms and components.
Scaling machine learning algorithms to work on massive data sets and strict SLAs.
Build and orchestrate model pipelines including feature engineering, inferencing and continuous model training.
Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop.
Collaborate with client facing teams to understand business context at a high level and contribute in technical requirement gathering.
Implement basic features aligning with technical requirements.
Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors.
Ensure highest quality of 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.
Uses bug tracking, code review, version control and other tools to organize and deliver work.
Participate in scrum calls and 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.

What You’ll Bring

A master's or bachelor’s degree in Computer Science or related field from a top university.
1-3 years’ hands-on experience in ML development.
Good understanding of the 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 DB's.
Knowledgeable of core CS concepts such as common data structures and algorithms.
Collaborate well with teams with different backgrounds / expertise / functions
Fluency in English
Client-first mentality
Intense work ethic
Collabrative spirit and probelm-solving approach

How you’ll grow:

Cross-functional skills development & custom learning pathways
Milestone training programs aligned to career progression opportunities
Internal mobility paths that empower growth via s-curves, individual contribution and role expansions

Perks & Benefits:

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well‑being, financial future, time away, and professional development. With robust skills‑building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you’ll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in India, visit ZS India office locations | Where we work | ZS.

Hybrid working model:

We are committed to giving our employees a flexible and connected way of working. A flexible and connected 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:

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers 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.

Considering applying?

At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems—the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. Learn more about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive.

If you’re eager to grow, contribute, and bring your unique self to our work, we encourage you to apply.

ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law.

To complete your application:

Candidates must possess or be able to obtain work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered.

NO AGENCY CALLS, PLEASE.

Find Out More At:

www.zs.com

ZS

Vacatures

AI Engineer - Machine Learning