Machine Learning Operations Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

We are seeking a talented individual for a Machine Learning DevOps Engineer who participates in the second half of the data science life cycle, with a focus on model deployment, monitoring, CICD, etc., in collaboration with internal business partners. This role is responsible for realizing value propositions through the successful operationalization of revenue impacting ML models. The successful candidate will be able to develop, test, and deploy models into production environments, establish model health metrics and monitoring, while identifying and prioritizing potential ideas and communicate them effectively. 

Job Description

Responsibilities

• Design, develop, and own the open-source data science and machine learning platform
• Work closely with data scientists and automate machine learning solutions, including building data pipelines, continuous delivery (CI/CD) using Jenkins, Docker, Kubernetes, etc.
• Site reliability and availability, including end-to-end performance, service monitoring, alerting, capacity sizing and planning
• Work with and support business partners in the use of DSML; business continuity planning and testing
• Support of production infrastructure and services, including our on-prem and cloud infrastructure.
• Persistence and willingness to learn and apply new techniques/new tools; provide leadership to the team in mastering technologies, identifying and implementing worthwhile new technologies and improving our processes.
• Ability to work independently and with minimal or no direction
• Entrepreneurial mindset to identify and solve problems and able to build prototypes/Minimal viable products
• Ability to move seamlessly between business problems and coding
• Good presentation skills to explain complicated analytical solutions to a non-technical group of people, internal or external

Job Requirements Qualifications

• Undergraduate degree in a technical field, such as Computer Science, Computer Engineering, Electrical Engineering or Mathematics
• At least 5 years of DevOps and system administration experience, preferably in small/mid-size corporate or mid/ late startups
• At least 3 years in managing Azure or AWS cloud infrastructure
• Expertise in Docker. Kubernetes would be an added advantage
• Linux administration (RHEL, Ubuntu) and scripting (e.g. shell script, Python)
• Hands on with programming skills, such as Python, Scala or Java
• Hands on with Hadoop-related technologies, MapReduce, Spark, Kafka, Hive, Impala, etc.
• Knowledge in scaling Machine learning solutions
• Soft skills, e.g. team player, clear and concise communication, problem solver, fast learner (our team runs like a startup)

Good to have

• A strong passion to identify and solve real business problems using data and machine learning
• Knowledge of analytical tools such as R, Python, SAS or other statistical packages
• Expertise in database scalability and availability, preferably with PostgreSQL and Redis
• Logging, Performance Monitoring (e.g. New Relic, DataDog, EFK/ELK)
• Knowledge of data visualization tools such as Tableau, Business Intelligence, Reporting and other advanced analytics tools and how they access data on different data stores
• Understanding of open source Machine Learning and Artificial Intelligence libraries such as Spark MLlib, H2o.ai, TensorFlow, etc.
• Working knowledge in large-scale/distributed SQL, Hadoop, NoSQL, HBase, Columnar databases
• Experience working with very large datasets which happen to be residing in different data stores in different formats
• Learn business problems and design and build ML/AI and Advanced Analytics models to solve them