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Engineering Lead/Machine Learning (Bangalore, India)

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 

  • Leads team to achieve established goals, such as delivering new features or functionality; 

  • Provides technical expertise including the evaluation of different products in ML Tech stack, designing ML Engineering components 

  • Collaborate with Data scientists to deliver scalable ML models 

  • Handle client interactions as and when required 

  • Drive major features and application-wide or system-wide changes working closely with the architect. For example, architecture redesign, use of new technologies 

  • Recommend designs that are scalable, testable, debuggable, robust, maintainable and usable 

  • Review individual work plans before implementation to identify potential issue areas and/or reduce rework 

  • Performs design / code reviews of the team to identify issues/risks and ensure robustness 

  • Drive estimation of technical components and tracks team's progress 

  • Drive technical discussions / demos / presentations with client stakeholders; 

  • Maintain a culture of rapid learning and explorations to drive innovations / POCs on niche technologies and architecture patterns; 

  • Mentor and groom technical talent within the team and expertise center; 

  • Breaks down large features into estimable tasks, leads estimation and tracks progress; 

  • Implement complex features with limited guidance 

  • Systematically debug code issues / bugs using stack traces, logs, monitoring tools, and other resources 

  • Performs code/script reviews of senior engineers in the team 

 

Qualifications 

  • 6-8 years experience in deploying and productionizing ML models at scale 

  • Ability to identify the right product, utilities and tools from the market and build quick POVs for implementation/adoption 

  • Experience in leading and mentoring ML engineers in the complete ML lifecycle 

  • Expertise in Designing, configuring and using ML Engineering platforms like Sagemaker, MLFlow, Kubeflow or other platforms 

  • Experience in Troubleshooting and tuning ML Models for high performance and scalability 

  • Building CI/CD pipelines and orchestration for feature engineering, model training & inferencing 

  • 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 deployment to cloud services like AWS, Azure, GCP 

  • Strong fundamentals of machine learning and deep learning 

  • Up to date with recent developments in Machine learning and are familiar with current trends in the wider ML community 

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

  • Excellent technical presentation skills (documentation, presentations, discussions) 

  • Good communicator with clear and concise, active listening and empathy skills. 

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

 

Additional Skills 

  • Understanding of DevOps, CI / CD, data security, experience in designing on cloud platform; 

  • Understanding of data governance 

  • Experience in data engineering in Big Data systems 

  • Willingness to travel to other global offices as needed to work with client or other internal project teams. 

 

ZS is a global consulting firm; fluency in English is required, additional fluency in at least one European or Asian language is desirable. 
Candidates must possess work authorization for their intended country of employment. An online application, including a cover letter expressing interest and a full set of transcripts (official or unofficial), is required to be considered.
ZS offers a competitive compensation package with salary and bonus incentives, plus an attractive benefits package.

NO AGENCY CALLS, PLEASE.

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ZS has been recognized globally for its expertise in consulting and its flexible work environment. View ZS’s accolades.