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At Onclusive, we are passionate about building software that solves important problems in marketing and communications. We partner with the most valuable companies in the world to transform how they use data and technology to drive marketing and brand decisions. Our software has been used to strategize responses to a brand crisis, discover new content and influencers, and gain an edge in the global online business world.
As a Machine Learning Ops Engineer, you will work on deploying, scaling, and optimizing backend algorithms, robust and scalable data ingestion pipelines, machine learning services, and data platforms to support analysis on vast amounts of text and analytics data. You will apply your technical knowledge and Big Data analytics on Onclusive’s billions of online content data points to solve challenging marketing problems. ML Ops Engineers are integral to the success of Onclusive.
- Design and build scalable machine learning services and data platforms.
- Utilize benchmarks, metrics, and monitoring to measure and improve services.
- The system currently processes data on the order of tens of millions of jobs per day.
- Research, design, implement and validate cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes.
- Work with data scientists and machine learning engineers to implement ML, AI and NLP techniques for article analysis and attribution.
- Deploy, manage, and optimize inference services on autoscaling fleets with GPUs and specialized inference hardware
- Work with technologies like Python, Java, Scala, Redis, ElasticSearch, Apache Spark, Kubernetes, Docker, etc.
- BS, MS, or Ph.D in Computer Science or related field and/or equivalent experience in the space.
- Software engineering experience.
- Familiarity with frameworks and models such as TensorFlow, TF Serving, ONNX Runtime, BERT, Kubeflow, MLflow
- Experience with machine learning pipelines and deployment.
- Experience with data processing frameworks such as Apache Spark and Flink is a bonus