Machine Learning Ops Engineer

As Machine Learning Ops Engineer you will own the production pipeline for all DS job, work closely with data science on new pipelines and create monitoring solutions around all aspects of pipeline, and more. Exciting opportunity for someone with strong MLOps and Data Engineering experience.

Responsibilities

Own production pipeline for all DS jobs; Work closely with data science on new pipelines; Create monitoring solutions around all aspects of pipeline; Scale solutions around data volumes, budget, SLAs, infrastructure; CI/CD pipeline ownership; Help Architect necessary data handoffs to other squads; Develop and mentor best practices within Impact; Interface with external systems to extract data; Operate independently, research new technologies, champion solutions; Collaborate cross squad to develop various data handoffs

Requirements

Masters in Computer Science, Data Science preferred; 3+ years experience in developing and deploying machine learning models in a production environment; 1+ year of experience in MLOps and Data engineering; Experience in Databricks preferred; Experience in all DS libraries; Google Cloud environment certifications a plus; Collaboration with squads, leadership role; Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.); Familiarity with DevOps practices and tools such as Kubernetes, Docker, Jenkins, Git; Strong DevOps mentality: Knowledge of making a complicated pipeline simple and easy to maintain, with proven experience of Terraform/Spark; Continuous Learner; Cloud / GCP experience; Big Data experience; Highly organized, proven ability to work on multiple projects at once; Problem Solving

Nice to have

Masters in Computer Science, Data Science preferred; Experience in Databricks preferred; Google Cloud environment certifications a plus; Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)

Benefits

Hybrid, Casual work environment; Responsible PTO policy; Primary caregiver leave; Training & Development; Learning the advanced partnership automation products; Medical Aid and Provident Fund; Group schemes with Discovery & Bonitas for medical aid; Group scheme for provident fund; Restricted Stock Units; 3-year vesting schedule pending Board approval; Internet Allowance; Fitness club fee reimbursements; Technology stipend