• American Express - Machine Learning Engineer - Big Data/Java Jobs in Bangalore,India

  • American Express

Job Description:

About Machine Learning Platform

- American Express Enterprise Machine Learning Platform provides Application Engineers, Data Scientists and Data Analysts a large scale comprehensive platform to pre-process large scale data from enterprise data lakes, train/build machine learning models and leverage the platform to predict/score using these models

- It provides its users a high performance compute environment on HDFS and GPUs to process large workload of data

- In addition to the open-source ML Libraries, it has custom-developed ML algorithms which are developed to be used enterprise-wide to develop ML models

- It has a custom-developed interface on Jupyter Notebook for its users to develop and deploy ML models

Whats in it for me?

- If you are among those who want to enhance your research/ work experience through machine learning and AI into to real life problems, working on large data, upcoming and new algorithms and excited in applying your computer science skills to innovate, design and implement solutions we encourage you to come and be a part of American Express Technology

- You will also get an opportunity to work on Big Data and employ ML techniques

- Our team comprises of highly motivated engineers, product managers and data-scientists building end-to-end web-scale and enterprise-scale AI/ML-enabled systems

- Together we will develop and deliver robust, state of art and scalable solutions across a rich set of scenarios

As a Machine Learning Engineer of the Machine Learning Platform Engineering team you will

- Enhance your research/ work experience through machine learning and AI into to real-life problems

- Working on large data, upcoming and new algorithms

- Apply your computer science skills to innovate, design and implement solutions using Machine Learning

- Implement Platform design to host the platform and application components in a secured and governed way

- Work on enabling the ML Platform to be Cloud Native by re-engineering the components to conform to Cloud Native

Foundation (CNF)

- Work on PaaS/Containers (Docker, Kubernetes) and IaaS (VMs) related technologies

- Have a focus on delivery following an Agile process

- Be passionate about quality metrics in product implementation


Required Qualifications

- Position requires a Bachelors Degree in Computer Science, Engineering, or a related field with good mathematical foundation followed by 5-6 years of industry experience building data-driven products and have implemented machine learning algorithms and techniques

- Good in Computer Science fundamentals in object-oriented design, data structures, algorithm design, complexity analysis, problem-solving and diagnosis

- Adept at any one of the programming language Java/Python and Open to learn new programming languages

- Comfortable in Big Data Technologies/ Frameworks (Hadoop, Spark, HDFS, Hive, Sqoop, Flume, Oozie, etc)

- Well conversant with Linux / Unix tools

- Experience working with distributed systems using Spark, Hive in Hadoop at significant scale in a production environment

- Well conversant with any one of version control capabilities like GitHub, bitbucket and SVN

- Good oral and written communication skills as well as interpersonal and multi-tasking skills

- BS/MS degree in Computer Science

Preferred Qualifications

- Experience in application development and integration within one or more Iaas/ Paas platforms such as (Amazon Web Services, VMWare, OpenStack, etc)

- Experience building fast and scalable machine learning and analytical algorithms and executing all tasks from design to deployment and monitoring

- Experience in developing Web services, micro-services, and REST

Job Type Permanent

Industry Type Digital Commerce

Contact Url https//jobsamericanexpresscom

The Apply Button will redirect you to website Please apply there as well


Profile Summary:

Employment Type : Full Time
Salary : Not Mentioned
Deadline : 20th Feb 2020

Key Skills:

Company Profile:

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