Machine Learning Operations Engineer

As a Machine Learning Operation Engineer at Onclusive, you will play a crucial role in deploying, scaling, and optimizing backend algorithms, data ingestion pipelines, machine learning services, and data platforms. Your expertise will be utilized to support the analysis of vast amounts of text and analytics data, helping to solve challenging marketing problems using Onclusive's billions of online content data points. Your responsibilities will include designing and building scalable machine learning services and data platforms, utilizing benchmarks and metrics to measure and improve services, managing systems processing tens of millions of jobs per day, researching and implementing cutting-edge algorithms, and collaborating with data scientists and machine learning engineers on ML, AI, and NLP techniques for article analysis and attribution. Additionally, you will deploy, manage, and optimize inference services on autoscaling fleets with GPUs and specialized inference hardware. The ideal candidate for this role will have a degree (BS, MS, or Ph.D.) in Computer Science or a related field, accompanied by hands-on experience. Proficiency in Python with a strong understanding of Object-Oriented Programming (OOP) principles is required. Knowledge of containerization (preferably Docker), experience with Kubernetes and Infrastructure as Code (IAC) for AWS (preferably Terraform), familiarity with Version Control Systems (VCS) like Git and GitHub, CI/CD (preferably GitHub Actions), and good understanding of ML principles are essential. Data Engineering experience and exposure to deep learning tech-stacks like Torch/Tensorflow and Transformers are highly desired. Onclusive offers a global, fast-growing environment with opportunities for skill development and career growth. In return for your contributions, you can expect a competitive salary and benefits, hybrid working arrangements, a supportive team passionate about their work, and a focus on wellbeing and work-life balance through initiatives such as flexible working and mental health support.,