The Fifth Elephant MLOps track
The Fifth Elephant which started in 2012 as an annual conference has now evolved into a community which focuses on shared learning around the theory and practice of big data and ML. The vibrant discussions provide community members with deep knowledge from experts who bring out emerging trends, challenges and directions of innovation.
The Fifth Elephant is rated among Asia’s best Machine Learning conferences. Hotstar, Uber, Ola, Gojek, Freshworks, Google, Tecton, InMobi, Cloudera, WalmartLabs, Salesforce and other organizations have shared experiential case studies on The Fifth Elephant’s platform.
MLOps is gaining immense popularity. The biggest driver for MLOps is the fact that a big portion of Machine Learning models (70-90% based on various reports) never make it to production, or fail before they even get there. It is no more a question of whether Machine Learning models are capable of delivering or not. It is now the question around business viability and impact. The economics around Machine Learning have led to MLOps taking centrestage. The hypothesis is that with the advent and implementation of MLOps as a culture in organizations, we will see more pragmatism in the expectations around Machine Learning and the realistic impact it can have on products, businesses and consumers. This will help build a sustainable ecosystem based on sane microeconomics.
The MLOps track is transitioning from being an annual conference under The Fifth Elephant umbrella to becoming a forum for continuous exchange of knowledge and engagement. The MLOps track will produce content in the form of 101s, guides and playbooks, podcasts and studio produced discussions and talks. MLOps is now redesigned to be continuously looking at trends, engaging with companies and practitioners to share success and failure stories and provide the interface between big data/AI based policy and community.
Editorial at MLOps track
Hasgeek tracks are led by Editors who have deep knowledge and experience of the industry. Nischal HP (VP - Data and ML - at Scoutbee) is the editor for MLOps track, and has been actively shaping the developments in this field. The EA will work with Nischal, and will gain immensely from collaborating with a thought leader in this space who is well-versed in technology, policy and consumer experience.
Responsibilities of the Editorial Assistant (EA) for MLOps track
The EA will be responsible for:
- Researching topics and experts - current and emerging - which will enrich the MLOps track.
- Provide themes and content for bi-monthly newsletter.
- Work with the editor and speakers to achieve milestones and outcomes.
- Produce AMAs, panel discussions, and conferences; auditing the outcomes.
- Publish written outputs such as 101 content, playbooks, blog posts, etc.
- Preferred candidates are those who have at least 2+ years’ work experience.
- Excellent written communication with strong ability to synthesize information.
- Ability to communicate effectively with internal and external stakeholders, and flexibility to adjust to a wide variety of working styles.
- Excellent organizational skills and attention to detail.
- Positive, collaborative approach to work.
- Understanding of the practical aspects of data engineering and Machine Learning, and/or demonstrable work on the sociology and business impacts of Machine Learning.
- MarComm or developer evangelism experience around ML and data engineering is beneficial for this job role. This job role will help you to develop a deep dive into understanding the industry and upcoming trends.
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