ML Ops Engineer

Responsibilities As a Senior Machine Learning Ops Platform Engineer, you will build automation and leading‑edge architecture around Data and AI/ML engineering on an AWS & Kubernetes platform. Your work will involve hands‑on code development, designing production‑grade scalable systems, and ensuring high‑quality coding and CICD practices across a team of engaged engineers. Key Responsibilities Build and maintain systems using DevOps & LLM Ops (Kubernetes, Docker), AWS, Python and Terraform. Stay informed of industry trends and enable successful DevOps/MLops AWS platform and Terraform solutions by leveraging best practices. Participate in and set up Proof of Concepts (POCs) to demonstrate proposed solutions. Enable team members through training, culture, and team building. Identify, design, and implement internal process improvements such as automating manual processes and redesigning infrastructure for greater scalability. Architect AWS infrastructure components (e.g., Lambdas, EC2, Docker, pipeline engineering, data monitoring alerting, networking). Build, design, implement, and support Data & ML model pipelines using the latest CICD and deployment technologies. Collaborate with stakeholders—including Executive, Product, Data, and Design teams—to resolve technical issues and support infrastructure needs. Participate in code review and continuous process improvement. Qualifications 7+ years of total experience in a complex, technical environment. Experience developing production‑grade code in Python, SQL & Pandas. Experience with 3 or more of the following AWS services: Lambda, EC2, EMR, S3, Glue, Athena, RDS, Networking, IAM, Batch processing, SageMaker, and Airflow. Experience with Terraform and commonly used DevOps tools and techniques such as Kubernetes, Docker, GitHub, GitHub Actions, CodePipeline, and Jenkins. Experience with Kubeflow & MLflow (advantage). Experience building and managing CI/CD pipelines and APIs. Experience with relational SQL and NoSQL databases; Snowflake experience is a plus. Experience working with AI/ML teams and cross‑functional teams in a dynamic environment. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 5–7+ years of professional experience in AI/ML development, ideally with ownership of production‑level AI systems. Proven experience at an AI‑first company or contributions to AI/ML research or open‑source projects (highly desirable). We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. #J-18808-Ljbffr