MLOps Engineer

Introduction
Our Software Networking Unit is looking for MLOps Engineers to join our development team of data scientists & data engineers to drive Artificial Intelligence & Machine Learning solutions for our data rich suite of software cloud networking products.

Your Role and Responsibilities
This role is primarily focused on developing ML solutions which leverage data from our products to drive insights and decision-making for our customers. The core responsibilities of the role involve supporting the automation development and implementation of machine learning and deep learning models management of big data infrastructure and execution of data engineering tasks. The successful candidate will be part of our AI/ML development team who design create and support AI-driven products to deliver impactful AI solutions.

Your role and responsibility will encompass:
– Experience in building training & deploying ML models and automation of these activities
– Programming in Java Python etc for automation of data extraction model training model deployment & production monitoring
– Building automated pipelines using CICD tools & technologies such as Jenkins Travis CI Kubernetes Ansible etc.
– Deploying solutions to cloud hosted systems such as IBM Cloud AWS Azure GCP etc.
– Diagnosing environmental issues and introduce/implement technologies to solve them
– Staying up-to-date on the latest container platform releases and containerization techniques
– Utilizing version control for maintaining codebase integrity and collaboration fostering a collaborative and error-free development environment
– Managing big data infrastructure and carrying out data engineering tasks ensuring efficient data storage processing and retrieval
– Staying up-to-date with the latest trends and advancements in AI/ML and related technologies and apply this knowledge to develop innovative solutions
– Ensuring that all solutions are developed with a focus on scalability reliability and performance

What we offer:

• Working for a top 5 IT company according to Forbes 2022 best employers ranking
• International and prestigious projects
• Highly skilled teams of experts
• Wide range of IBM trainings and certificates
• Access to Udemy Harvard Business Review O’Reilly Interskill IBM AI Skills Academy

And what is more:

• Contract of employment
• Competitive compensation – salary range depending on your skills and experience
• Private medical care and life insurance
• Employee Assistance Program
• Sport charity & other networking groups
• Summer/winter camps for children
• Discounts with IBM employee badge
• Referral Bonus Program
• Home office option
• No dress code

Required Technical and Professional Expertise
• 5+ years experience in AI/ML model development and/or deployment of AI/ML workloads
• Experience designing & developing automated pipelines for data extraction ML model training ML model production deployments and production monitoring
• Hands-on experience from industry projects and actual validation of models for the operation scalable deployment and operation and monitoring of machine learning applications for end users
• Background in developing and implementing automation frameworks and strategies
• Proficient in Python with experience in coding and debugging in Python
• Hands-on experience with a cloud computing platform such as IBM Cloud AWS Azure or GCP
• Experience with DevOps practices and tools such as Docker Kubernetes and CI/CD pipelines
• Experience with big data technologies such as Hadoop Spark and NoSQL databases
• Linux skills preferably in RHEL
• Knowledgeable in applying security practices/techniques in containerized and non-containerized solutions
• Fluent in written and spoken English

Preferred Technical and Professional Expertise
• Hands-on experience with machine learning techniques and tools including but not limited to: TensorFlow PyTorch scikit-learn and XGBoost
• Familiarity in multiple programming languages (Python Java) demonstrating versatility and adaptability is a plus
• Certification in data engineering machine learning or AI