Machine Learning Engineer | Gurgaon/Mumbai/Pune/Bengaluru- Onsite | 2+ yrs

The project focuses on conceptualizing, designing, and implementing a wide spectrum of Digital and Analytic solutions to improve commercial and operational effectiveness for clients. We offer a wide range of services based on client needs from strategy development, and roadmap definition to providing platforms and services that help clients with their ongoing operations. Our team possesses deep expertise in formulating strategies and delivering leading Digital and Advanced Analytics, Business Intelligence, and Platform Development to solve business problems.

A Machine Learning Engineer will be responsible for leading teams in client projects to deliver many of the responsibilities described below.

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 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, and 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.

• Minimum 3 years’ experience in deploying and productionizing ML models
• Bachelor’s degree
• 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 PySpark , 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 cloud platform;
• 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.