Senior Engineer/Machine Learning (Bangalore, India)
Bengaluru, Karnataka, India
1d ago

Job Description

ZS is a professional services firm that works side by side with companies to help develop and deliver products that drive customer value and company results.

From R&D to portfolio strategy, customer insights, marketing and sales strategy, operations and technology, we leverage our deep industry expertise and leading-edge analytics to create solutions that work in the real world.

Our most valuable asset is our people a fact that’s reflected in our values-driven organization in which new perspectives are integral and new ideas are celebrated.

ZSers are passionately committed to helping companies and their customers thrive in industries ranging from healthcare and life sciences, to high-tech, financial services, travel and transportation, and beyond.

ZS’s India Capability & Expertise Center (CEC) houses more than 60% of ZS people across three offices in New Delhi, Pune and Bengaluru.

Our teams work with colleagues across North America, Europe and East Asia to create and deliver real world solutions to the clients who drive our business.

The CEC maintains standards of analytical, operational and technological excellence across our capability groups. Together, our collective knowledge enables each ZS team to deliver superior results to our clients.

ZS's Digital & Technology group helps companies define and execute their technology strategy by designing, building, and operating their business intelligence (BI), cloud, data management, dashboard, and analytics capabilities.

Team members strategize, design and build custom IT solutions to improve our clients’ commercial effectiveness.

ZS’s Architecture & Engineering Expertise Center Group brings deep specialization across niche technologies with skills to play as hands-on developer, designer, and architect roles.

Team members will be expected to rapidly learn new technologies and become experts with industry-certified credentials. A large portion of EC members is expected to drive research and asset development as part of ZS’ Enterprise Services Center of Excellence (ESCOE), while others would be part of client teams, pod teams, or practice teams supporting client projects and solutions based on dominant technologies used in respective teams / clients while also staying abreast with everything happening in ESCOE to bring new ideas and technologies to their teams.

ZS's Scaled AI practice is part of ZS rich and advanced AI ecosystem, in the Architecture & Engineering Expertise Center, focused on creating continuous business value for clients using a range of innovative machine learning, deep learning, and engineering capabilities.

Being part of Scaled AI practice allows you to collaborate with data scientists to create state-of-the-art AI models, create and use cutting-edge ML platforms, create and deploy advanced ML pipelines and manage the complete ML lifecycle.

Responsibilities -

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 the 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 the 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.

  • 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 the latest technologies through rapid learning, conducting proofs-of-concept, and creating prototype solutions
  • Qualification & Experience -

    2-4 years experience in deploying and productionizing ML models

    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 with Spark or other distributed computing frameworks

    Strong programming expertise in Python, Scala or Java

    Experience in ML platforms like Sagemaker, MLFlow, Kubeflow or other platforms

    Experience in deploying models to cloud services like AWS, Azure, GCP

    Good fundamentals of machine learning and deep learning

    Knowledgeable of core CS concepts such as common data structures and algorithms

    Collaborate well with teams with different backgrounds / expertise / functions.

    Additional Skills -

  • Understanding of DevOps, CI / CD, data security, experience in designing on the cloud platform
  • AWS Solutions Architect certification with an understanding of broader AWS stack
  • Knowledge of data modeling and data warehouse concepts
  • Willingness to travel to other global offices as needed to work with the client or other internal project teams
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