Machine Learning Engineer

ZS is a place where passion changes lives. As a management consulting and technology firm focused on transforming global healthcare and beyond, our most valuable asset is our people.

Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping solutions from start to finish.

At ZS, we believe that making an impact demands a different approach; and that’s why here your ideas elevate actions, and here you’ll have the freedom to define your own path and pursue cutting-edge work.

We partner collaboratively with our clients to develop products that create value and deliver company results across critical areas of their business including portfolio strategy, customer insights, research and development, operational and technology transformation, marketing strategy and many more.

If you dare to think differently, join us, and find a path where your passion can change lives. Our most valuable asset is our people.

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 andmake us unique.

We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about.

Machine Learning Engineer

AI Practice

ZS AI Practice is building transformative AI-enabled data products and solutions. ZS suite of products and solutions include hyper-personalization, Customer journey design, AI guided selling, large-scale unstructured customer data mining with NLP and dynamic pricing.

Our products and client focused solutions use state of the art ML and Deep Learning techniques and ML Engineering Platforms.

What You’ll Do

• Build, orchestrate, and monitor model pipelines including feature engineering, inferencing and continuous model training
• Scaling machine learning algorithms to work on massive data sets and strict SLAs
• Build & Enhance ML Engineering platforms and components
• Implement ML Ops including model KPI measurements, tracking, data and model drift & model feedback loop
• 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
• Collaborate with client teams and global development team to successfully deliver projects
• Uses bug tracking, code review, version control and other tools to organize and deliver work
• Participate in scrum calls, and effectively communicate work progress, issues and dependencies
• Consistently contribute to researching & evaluating latest architecture patterns / technologies through rapid learning, conducting proof-of-concepts and creating prototype solutions.

What You’ll Bring

• Bachelor's / Master's degree with specialization in Computer Science, MIS, IT or another computer related discipline
• 2-4 years' experience in deploying and productionizing ML models
• Strong programming expertise in Python / PySpark
• Experience in ML platforms like Dataiku, Sagemaker, MLFlow or other platforms
• Experience in deploying models to cloud services like AWS, Azure, GCP
• 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
• Good fundamentals of machine learning and deep learning
• Knowledgeable of core Computer Science concepts such as common data structures, algorithms, and design patterns
• Excellent oral and written communication skills

Additional Skills

• Experience with Spark or other distributed computing frameworks
• Understanding of DevOps, CI / CD, data security, experience in designing on cloud platform
• Experience in data engineering in Big Data systems

Perks & Benefits : 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 and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member.

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.