Machine Learning Engr

Key Skills

JavaScript, Java Programming, Analytical and Problem solving, Microsoft Office suites, Design, AngularJS, Python Programming, C++, C Programming, SQL, XML-JSON, React.js, Azure, AWS, Openstack, DXP solutions, Apache Kafka, NoSQL, Apache Hive, Apache Airflow, Google Cloud Platform (GCP), HDFS, Terraform, Prometheus, Grafana, Kibana, Kubeflow, MLflow, SPARK Programming, Amazon Simple Storage Service (S3), Large scale data processing, Cloud Security Analytics, Data Architecture, UML

Job Description

The AI team is responsible for designing and developing the next generation Machine Learning and AI / Cloud architecture for our tools. Towards this end, we are looking for a software engineer with expertise in microservices architecture, containers, distributed systems, webservers fine-tuning, and API design who can help develop and deploy robust software components that meet our high-quality requirements both on-prem and in public cloud.

Responsibilities

• Responsible for designing, developing, troubleshooting, or debugging on-prem and cloud infrastructure for ML/AI based tools and applications.
• This role may span multiple tiers such as data management, backend services, visualization, and presentation, as well as APIs for the infrastructure.
• The candidate will work with other members of the engineering team to identify and implement optimal solutions. Must have a strong background and proven track record in developing such applications and be able to create best practices and guidelines.
• The Software Engineer is expected to exercise judgment in selecting methods and techniques to obtain solutions, and work on problems of diverse scope where analysis of situations or data requires evaluation of various factors.
• Can perform with little or no instructions on day-to-day work, and with occasional general instructions on new assignments and projects. Is able to work both independently and collaboratively. Provides regular updates to manager on project status.

Requirements

• BS/MS EE/CS/CE with a minimum of 3+ years of experience developing large scale architectures and distributed systems
• Experience in designing and deploying cloud native micro services application on Kubernetes both on-prem and public clouds
• Experience in microservices architecture based design and implementation
• Hands-on experience in one or more languages such as C/C++, Python, Java, JavaScript, XML, UML, JSON
• Experience with containerization, distributed computing, fault tolerance, throughput and latency tuning, CI/CD pipelines
• Experience in datastores (one or more of SQL, No-SQL, S3 object stores, columnar, time series, in memory, etc)
• Strong background in file systems, data structures, algorithms, performance, and scalability. Demonstrates good analysis and problem-solving skills
• Ability to work independently, and exceptional verbal/written communication, leadership, interpersonal, and teamwork skills are a must

Desired skills

• Experience in working in Data Engineering tools such as Kafka, Spark, Hive, HDFS, Airflow, MLFlow, Kubeflow, ActiveMQ, Prometheus, Grafana, Kibana, GUI Technologies (Angular, React, GWT)
• Experience in API design, security, Identity & Access Management
• Experience in working (configuring, deploying, managing, and monitoring) with AWS, GCP, and/or Microsoft Azure, experience with Terraform and/or Cloud Formation
• Experience in machine learning and deep learning, ML model versioning and deployment.
• Cloud certifications are a plus: AWS Solutions Architect, Cloud Security Certification, OpenStack Certification
• Solid understanding of storage platforms and leading technology vendors