Job Description

AI Engineer (Fully Onsite)
Location: San Francisco, CA
Length: 22 month contract

Overview:
AI Engineer role is responsible for developing scalable AI solutions aligned to a business strategy and benefits case. The role will be to work as part of a team to impact real world problems by delivering technical AI work. To be successful in this role you will need to be passionate about Data & AI, a continuous learner, and a strong team player.

Responsibilities:

• Customer onboarding, nominations, and vetting processes
• Proof of Concept design, lab scheduling, and monitoring of overall governance of AI Studio
• Provide Studio tours, manage demo showcase, and process improvements
• Conduct customer satisfaction surveys and share key learnings, run customer engagement reports and project retrospective reports as well as provide Studio summary for customer & logging product bugs with engineering team
• Produce innovative solutions for our clients driven by exploratory data analysis from complex and high-dimensional datasets, both structured and unstructured, applying advanced statistical, machine-learning and AI techniques.
• Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data.
• Communicate insights and deliver plans that steer business strategy and decision-making for one or more business segments.

Skills and experiences:

• Possess a degree in Applied Mathematics, Statistics, Analytics, Economics/Econometrics, Engineering or another relevant field in the industry. An equivalent combination of education and experience will also suffice.
• 1-2 years of demonstrable experience across the advanced analytics space, preferably in a consulting environment or a combination of experience and relevant education.
• Demonstrable professional experience with applying Machine Learning, analysis, and modeling of large scale and complex data sets in Industry scenarios.
• Highly skilled in statistical analysis, quantitative analytics, forecasting/predictive analytics, simulation and optimization algorithms.
• Proficient in one or more statistical modeling tools and Cognitive analytics like text analytics, image recognition, video analytics etc.- proficient in model identification by use case/industry and knowledge of applying models to enterprise use cases.
• Highly proficient with two or more languages, such as Python, PySpark, R, SQL, etc. and tools like Databricks, Azure ML and Azure Cognitive Services
• Software engineering experience using DevOps principals (Knowledge of DevOps workflows, Git, containers, CICD, etc.)
• Good communication and presentation skills. Able to explain complex analytical methodologies and concepts in non-technical language to audiences at multiple skill levels.
• Bonus Skills: Preference for prior experience working with Azure or cloud-based technologies such as AWS or Google Cloud Platform but not required.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

• Dice Id: cybersea
• Position Id: CYB-17474

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