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Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Our company of 2000+ employees has presence across 12 global locations, including the United States, UK, Australia, Switzerland, Singapore, Canada, China, Germany, Sweden, the Netherlands, Ukraine and India.
15 жовтня 2020

ML Engineer (Azure) (вакансія неактивна)

Київ

Overview:

Fractal is looking for people who are passionate around solving business problems through innovation and engineering practices. You’ll be required to apply your depth of knowledge and expertise to all aspects of the analytical problem solution lifecycle, as well as partner continuously with your many stakeholders on a daily basis to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning. You’ll work in a collaborative, trusting, thought-provoking environment-one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally.

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 cloud computing platforms: Google Cloud, Amazon Web Service, Azure, Kubernetes.
• Experience in Azure cloud services (especially Azure Devops) and deploying production code in the same
• 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
• Expertise in standard concepts and technologies used in CI/CD build, deployment pipelines
• Experience with scripting and coding using Python, Shell
• Experience in Azure ecosystem — Azure data bricks, Azure Devops and Azure ML Services would be preferred.
• 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

We offer:
Best team: multicultural team of bright specialists and friendly, helping people (data scientists, ML/AI specialists, data engineers, developers, business analysts, QA team, as well as internal support staff);
Challenge: plenty of complex and exciting projects from international clients;
Income: competitive salary and end-year bonuses;
Travelling: possibility to travel onshore and clients’ side;
Learning and professional development: access to company learning platforms with free courses, external certifications and learning programs;
Being healthy: free insurance after probation period; paid vacation;
Communication: company parties, celebrations, workshops in different locations, cross-locations and cross-projects exchange programs.