Senior Machine Learning Operations Engineer

Role Overview: As a Machine Learning Operation Engineer at Onclusive, your primary responsibility will be to deploy, scale, and optimize backend algorithms, robust data ingestion pipelines, machine learning services, and data platforms to handle vast amounts of text and analytics data. You will leverage your technical expertise and Big Data analytics skills to address complex marketing challenges using Onclusive's extensive online content data. The role of an ML Ops Engineer is crucial to the success of Onclusive. Key Responsibilities: - Designing and constructing scalable machine learning services and data platforms - Utilizing benchmarks and metrics to enhance services - Overseeing a system processing tens of millions of jobs daily - Researching and implementing cutting-edge algorithms for data analysis - Collaborating with data scientists and ML engineers on implementing ML, AI, and NLP techniques - Managing inference services on autoscaling fleets with GPUs and specialized hardware Qualifications Required: - Hold a degree (BS, MS, or Ph.D.) in Computer Science or a related field - Minimum of 2 years of experience with Kubernetes and/or Terraform - Proficiency in Python with a solid grasp of Object-Oriented Programming principles - Knowledge of containerization (preferably Docker) and Infrastructure as Code (IAC) for AWS (preferably Terraform) - Familiarity with Version Control Systems (particularly Git and GitHub) and CI/CD (preferably GitHub Actions) - Understanding of release management with a focus on testing and quality assurance - Good grasp of ML principles - Desirable experience in Data Engineering tools like airflow, dbt, and meltano - Exposure to deep learning tech-stacks such as Torch, Tensorflow, and Transformers is a plus Additional Details: Omit (No additional details mentioned in the provided Job Description),