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ML Engineer

3.00 to 5.00 Years   Bangalore   03 Nov, 2020
Fractal Analytics
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryKPO / Analytics
Functional AreaGeneral / Other Software
EmploymentTypeFull-time

Job Description

  • As an ML Engineer, you will work collaboratively with Data Scientists and Data engineers to deploy and operate systems.
  • You ll help automate and streamline our operations and processes.
  • You ll build and maintain tools for deployment, monitoring, and operations.
  • You ll also troubleshoot and resolve issues in development, testing, and production environments
Responsibilities:
  • Operate and maintain systems supporting the provisioning of new clients, applications, and features.
  • Day-to-day monitoring of the Production service delivery environment to ensure all services and applications are operating optimally and SLAs are met.
  • Software deployment and configuration management in both QA and Production environments.
  • Collaborate with Data Scientists and Data Engineers on feature development teams to containerize and build out deployment pipelines for new modules
  • Design, build and optimize applications containerization and orchestration with Docker and Kubernetes and AWS or Azure
  • Automate applications and infrastructure deployments.
  • Produce build and deployment automation scripts to integrate between services
  • Be a subject matter expert on DevOps practices, CI/CD and Configuration Management with assigned engineering team
  • Experience with one of the cloud computing platforms: Google Cloud, Amazon Web Service, Azure, Kubernetes.
  • Experience in MLFlow, Qubeflow, MLTracking, MLExperiments
  • Experience in big data technologies preferred: Hadoop, Hive, Spark, Kafka.
  • Knowledge of machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, Scikit-Learn.
Skills:
  • At least 3 years experience working with cloud-base services and DevOps concepts, tools and practices
  • Extensive experience with Unix/AIX/Linux environments
  • Experience with Kubernetes or Docker Swarm
  • Experience working in cross-functional Agile engineering teams
  • Familiarity with standard concepts and technologies used in CI/CD build, deployment pipelines
  • Experience with scripting and coding using Python, Shell
  • Experience with configuration using tools such as Chef, Ansible
  • Experience with automation servers such as Jenkins, CloudBees, Travis
  • Experience with logging tools such as Splunk, ElasticSearch, Kibana, Logstash
  • Experience with monitoring tools such as Munin, Prometheus, Grafana, AlertManager, PagerDuty
  • Big data technical stack experience is a plus such as HDFS, Spark, Ambari, ZooKeeper, Kafka
  • Excellent Written and Verbal Communication Skills
  • Ability to collaborate effectively with highly technical resources in a fast-paced environment
  • Ability to solve complex challenges/problems and rapidly deliver innovative solutions
,

Keyskills :
verbal communicationconfiguration managementservice deliverymonitoring toolscloud computingbig datamachine learningcreative solutions

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