Job Title: MLOps + DevOps (Platform) EngineerLocation: Remote / HybridJob Type: Full-timeAbout the RoleChapter 2 is working with a leading creative agency to develop scalable machine learning platforms for AI-driven content creation. This role is perfect for an MLOps + DevOps Engineer who thrives in fast-paced environments, takes ownership, and has experience building infrastructure for large-scale AI and ML applications. You'll be instrumental in developing automated, scalable, and high-performance ML infrastructure to support generative AI workflows and large language models (LLMs) in production.What Youll DoDesign, build, and maintain scalable ML platforms for model development, experimentation, and production workflows.Automate ML infrastructure deployment, including data pipelines, model training, validation, and deployment.Manage the full ML lifecycle, from model versioning to deployment, monitoring, and retraining.Optimise large language model (LLM) operations, ensuring efficient fine-tuning, deployment, and performance monitoring.Collaborate closely with data scientists and engineers to develop and deploy ML models at scale.Optimise performance for inference and training across GPUs and cloud-based architectures.Ensure security and compliance for ML platforms handling sensitive data.Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency.Implement monitoring and alerting systems to detect anomalies and maintain model reliability.What Were Looking For3+ years of experience in software engineering, infrastructure, or MLOps roles.Proven expertise in building and maintaining ML platforms at scale.Hands-on experience with cloud platforms (AWS, GCP, or Azure) for ML workloads.Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation).Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch.Experience designing CI/CD pipelines for ML workflows and deployment automation.Exposure to LLM Ops, including managing fine-tuning and deployment of large language models.Strong problem-solving skills and ability to troubleshoot complex ML infrastructure issues.Ability to work in a fast-paced, high-growth environment with a product-oriented mindset.Bonus: Experience with big data tools (Spark, Kafka) and feature stores.Why Join Us?Work on cutting-edge AI and ML infrastructure supporting generative AI products.Be part of a high-impact, innovative team driving AI advancements.Competitive salary, benefits, and career growth opportunities.Collaborate with top-tier engineers and data scientists in the AI space.Excited? Lets talk. Apply now with your resume and portfolio!
Job Title
Platform Engineer