Data Scientists/MLOps Engineer to deliver strategic solutions in AI/ML space. This includes development of systems that serve ...
Data Scientists/MLOps Engineer to deliver strategic solutions in AI/ML space. This includes development of systems that serve ML models in production, systems automation and delivery of toolsets used in AI/ML lifecycle.
Long Term Rate $620per day (Corp to corp) - 8 hour day)
Location: Initially Remote, but will be onsite when rules dictate return to office in Raleigh NC.
• possibility to architect business focused big data, analytical and ML solutions in finance sector
• rapidly evolving data science, data engineering and machine learning projects
• flexible, friendly and multicultural working environment
• possibility to develop your skills AI/ML space
• possibility to develop large scale, distributed, fault-tolerant software systems and infrastructure
• strong programming and system engineering skills (advanced in Python programming and Linux administration)
• understanding of distributed systems design and patterns (APIs implementation, microservices, cloud - AWS/Azure/Google Cloud Platform)
• experience with container based solutions (Docker, Openshift/Kubernetes)
• knowledge about Agile, CI/CD and DevOps principles
• open mindedness and ability to think outside the box
• have a "whatever it takes" attitude to meet the engineering challenges
• self-motivated and comfortable operating in a global team interaction model (fluent English required)
• bonus points: experience in delivering ML models into production, ML/AI model development lifecycle, Cloudera
Big Data stack
The project on which candidate will work is an software/application implementation endeavor. Application itself is a tool to be used by Data Stewards and Data Scientists for governing Machine Learning models lifecycle. Hence the required skillset is encompassing generic application implementation/ systems integration knowledge and Machine Learning knowledge - python, models features, models metrics. As we are hiring couple of individuals, there is certain flexibility in actual skillset, as we might get to a full setup on a team level, not within each individual.
MIAC [Machine Intelligence and Accelerated Computing] team is part of DAIS [Data and Artificial Intelligence Solutions] department, under CIO and CDO reporting lines. We are a Credit Suisse CoE for Machine Learning: delivering business oriented Data Science projects and commoditizing algorithms on multiple platforms / tools. We work with both small and Big Data, taking advantage of our Big Data platforms stack (in DAIS as well).