Automation Test Engineer

Requirements

• Extensive and expert programming experience in at least one general programming language (e. g. Java, C, C++) & tech stack to write maintainable, scalable, unit-tested code.

• Experience with multi-threading and concurrency programming.

• Extensive experience in object oriented design skills, knowledge of design patterns, and a huge passion and ability to design intuitive modules and class-level interfaces.

• Excellent coding skills - should be able to convert design into code fluently.

• Knowledge of Test Driven Development.

• Good understanding of databases (e. g. MySQL) and NoSQL (e. g. HBase, Elasticsearch, Aerospike etc).

• 4+ years of experience in the art of writing code and solving problems on a large scale.

• Open communicator who shares thoughts and opinions frequently, listens intently, and takes constructive feedback.

Role: Data Engineer  
Company: PayU

Location: Bangalore/ Mumbai

Experience : 2-5 yrs

About Company:

PayU is the payments and fintech business of Prosus, a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities.

The leading online payment service provider in 36 countries, PayU is dedicated to creating a fast, simple and efficient payment process for merchants and buyers. Focused on empowering people through financial services and creating a world without financial borders where everyone can prosper, PayU is one of the biggest investors in the fintech space globally, with investments totalling $700 million- to date. PayU also specializes in credit products and services for emerging markets across the globe. We are dedicated to removing risks to merchants, allowing consumers to use credit in ways that suit them and enabling a greater number of global citizens to access credit services.

Our local operations in Asia, Central and Eastern Europe, Latin America, the Middle East, Africa and South East Asia enable us to combine the expertise of high growth companies with our own unique local knowledge and technology to ensure that our customers have access to the best financial services.

India is the biggest market for PayU globally and the company has already invested $400 million in this region in last 4 years. PayU in its next phase of growth is developing a full regional fintech ecosystem providing multiple digital financial services in one integrated experience. We are going to do this through 3 mechanisms: build, co-build/partner; select strategic investments. 

PayU supports over 350,000+ merchants and millions of consumers making payments online with over 250 payment methods and 1,800+ payment specialists. The markets in which PayU operates represent a potential consumer base of nearly 2.3 billion people and a huge growth potential for merchants. 

Job responsibilities:

• Design infrastructure for data, especially for but not limited to consumption in machine learning applications 
• Define database architecture needed to combine and link data, and ensure integrity across different sources 
• Ensure performance of data systems for machine learning to customer-facing web and mobile applications using cutting-edge open source frameworks, to highly available RESTful services, to back-end Java based systems 
• Work with large, fast, complex data sets to solve difficult, non-routine analysis problems, applying advanced data handling techniques if needed 
• Build data pipelines, includes implementing, testing, and maintaining infrastructural components related to the data engineering stack.
• Work closely with Data Engineers, ML Engineers and SREs to gather data engineering requirements to prototype, develop, validate and deploy data science and machine learning solutions

Requirements to be successful in this role: 

• Strong knowledge and experience in Python, Pandas, Data wrangling, ETL processes, statistics, data visualisation, Data Modelling and Informatica.
• Strong experience with scalable compute solutions such as in Kafka, Snowflake
• Strong experience with workflow management libraries and tools such as Airflow, AWS Step Functions etc. 
• Strong experience with data engineering practices (i.e. data ingestion pipelines and ETL) 
• A good understanding of machine learning methods, algorithms, pipelines, testing practices and frameworks 
• Preferred) MEng/MSc/PhD degree in computer science, engineering, mathematics, physics, or equivalent (preference: DS/ AI) 
• Experience with designing and implementing tools that support sharing of data, code, practices across organizations at scale 

• Preferred Education & Experience:

• Bachelor’s or master’s degree in Computer Engineering, Computer Science, Computer Applications, Mathematics, Statistics or related technical field or equivalent practical experience. Relevant experience of at least 3 years in lieu of above if from a different stream of education.

• Well-versed in and 5+ years of hands-on demonstrable experience with:
  ▪ Object Oriented Modeling, Design, & Programming
  ▪ Microservices Architecture, API Design, & Implementation
  ▪ Relational, Document, & Graph Data Modeling, Design, & Implementation

• Well-versed in and hands-on demonstrable experience with:
  ▪ Stream & Batch Big Data Pipeline Processing
  ▪ Distributed Cloud Native Computing
  ▪ Serverless Computing & Cloud Functions

• 5+ years of hands-on development experience in Java programming.

• 3+ years of hands-on development experience in one or more libraries & frameworks such as Spring Boot, Apache Camel, Akka, etc.;
  extra points if you can demonstrate your knowledge with working examples.
  2+ years of hands-on development experience in one or more Relational and NoSQL datastores such as Amazon S3, Amazon DocumentDB, Amazon Elasticsearch Service, Amazon Aurora, AWS DynamoDB, Amazon Athena, etc.

• 2+ years of hands-on development experience in one or more technologies such as Amazon Simple Queue Service, Amazon Kinesis, Apache Kafka, AWS Lambda, AWS Batch, AWS Glue, AWS Step Functions, Amazon API Gateway, etc.

• 2+ years of hands-on development experience in one or more technologies such as AWS Developer Tools, AWS Management & Governance, AWS Networking and Content Delivery, AWS Security, Identity, and Compliance, etc.

• Well-versed in Virtualization & Containerization; must demonstrate experience in technologies such as Kubernetes, Istio, Docker, OpenShift, Anthos, Oracle VirtualBox, Vagrant, etc.

• Well-versed with demonstrable working experience with API Management, API Gateway, Service Mesh, Identity & Access Management, Data Protection & Encryption.

• Hands-on experience with demonstrable working experience with DevOps tools and platforms viz., Jira, GIT, Jenkins, Code Quality & Security Plugins, Maven, Artifactory, Terraform, Ansible/Chef/Puppet, Spinnaker, etc.

• Well-versed with Storage, Networks and Storage Networking basics which will enable you to work in a Cloud environment.

•  Experience : 5+Years

• Job Location : Remote/Pune

Job Title: Chief Engineer: Deep Learning Compiler Expert

You will collaborate with experts in machine learning, algorithms and software to lead our effort of deploying machine learning models onto Samsung Mobile AI platform.

In this position, you will contribute, develop and enhance our compiler infrastructure for high-performance by using open-source technology like MLIR, LLVM, TVM and IREE.

Necessary Skills / Attributes:

• 6 to 15 years of experience in the field of compiler design and graph mapping.
• 2+ years hands-on experience with MLIR and/or LLVM.
• Experience with multiple toolchains, compilers, and Instruction Set Architectures.
• Strong knowledge of resource management, scheduling, code generation, and compute graph optimization.
• Strong expertise in writing modern standards (C++17 or newer) C++ production quality code along test-driven development principles.
• Comfortable and experienced in software development life cycle - coding, debugging, optimization, testing, and continuous integration.
• Familiarity with parallelization techniques for ML acceleration.
• Experience working on and contributing to an active compiler toolchain codebase, such as LLVM, MLIR, or Glow.
• Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, recurrent networks, etc.
• Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, Tensorflow or Caffe.
• Experience operating in a fast-moving environment where the workloads evolve at a rapid pace.
• Understanding of the interplay of hardware and software architectures on future algorithms, programming models and applications.
• Experience developing innovative architectures to extend the state of the art in DL performance and efficiency.
• Experience with Hardware and Software Co-design.

M.S. or higher degree, in CS/CE/EE or equivalent with industry or open-source experience.

Work Profile:

• Design, implement and test compiler features and capabilities related to infrastructure and compiler passes.
• Ingest CNN graphs in Pytorch/TF/TFLite/ONNX format and map them to hardware implementations, model data-flows, create resource utilization cost-benefit analysis and estimate silicon performance.
• Develop graph compiler optimizations (operator fusion, layout optimization, etc) that are customized to each of the different ML accelerators in the system.
• Integrate open-source and vendor compiler technology into Samsung ML internal compiler infrastructure.
• Collaborate with Samsung ML acceleration platform engineers to guide the direction of inferencing and provide requirements and feature requests for hardware vendors.
• Closely follow industry and academic developments in the ML compiler domain and provide performance guidelines and standard methodologies for other ML engineers.
• Create and optimize compiler backend to leverage the full hardware potential, efficiently optimizing them using novel approaches.
• Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues.
• Contribute to the development of machine-learning libraries, intermediate representations, export formats and analysis tools.
• Communicate and collaborate effectively with cross-functional hardware and software engineering teams.
• Champion engineering and operational excellence, establishing metrics and processes for regular assessment and improvement.

Keywords to source candidates

Senior Developer, Deep Learning, Prediction engine, Machine Learning, Compiler