Senior 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 technical expertise will be utilized to analyze vast amounts of text and analytics data to tackle challenging marketing problems. Your contributions as an ML Ops Engineer are essential to the success of Onclusive. Your responsibilities will include: - Designing and building scalable machine learning services and data platforms. - Utilizing benchmarks, metrics, and monitoring to measure and enhance services. - Managing systems processing tens of millions of jobs per day. - Researching, designing, implementing, and validating cutting-edge algorithms for data analysis. - Collaborating with data scientists and machine learning engineers to implement ML, AI, and NLP techniques. - Deploying, managing, and optimizing inference services on autoscaling fleets with GPUs and specialized hardware. To be successful in this role, you should possess: - A degree (BS, MS, or Ph.D.) in Computer Science or a related field, with hands-on experience. - Minimum of 2 years of experience with Kubernetes/Terraform. - Proficiency in Python and understanding of Object-Oriented Programming principles. - Solid knowledge of containerization, with Docker experience preferred. - Familiarity with Kubernetes and Infrastructure as Code (IAC), particularly for AWS using Terraform. - Experience with Version Control Systems like Git/GitHub and CI/CD tools, preferably GitHub Actions. - Understanding of release management, testing, validation, and quality assurance. - Good grasp of ML principles and desirable experience in Data Engineering (e.g., airflow, dbt, meltano). - Exposure to deep learning tech-stacks such as Torch/Tensorflow and Transformers. Onclusive, a global fast-growing company, offers a range of opportunities for your skill set and career development. In return for your contributions, we provide: - Competitive salary and benefits - Hybrid working environment with a team passionate about their work and supporting each other's development - Company focus on wellbeing, work-life balance, flexible working, and mental health support.,