AI Engineer – Sfl Scientific

AI Engineer role at Deloitte's SFL Scientific, focusing on developing and deploying AI infrastructure and services for machine learning applications. The role involves designing data architectures, supporting AI/GenAI use cases, and ensuring scalability, security, and high availability of solutions, working with clients across various industries.

What you'd actually do

  1. Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  2. Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  3. Participate in the design and development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  4. Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  5. Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem

Skills

Required

  • modern data architecture
  • data science engineering
  • data transformation
  • management of structured and unstructured data sources
  • cloud computing
  • on-prem technologies
  • data security
  • documentation
  • engineering architecture
  • automation
  • HPC

Nice to have

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

What the JD emphasized

  • robust AI infrastructure and deployment services
  • constructing IT infrastructure
  • scalable, high-performance data architecture solutions
  • AI/GenAI use cases
  • AI/GenAI infrastructure

Other signals

  • develop robust AI infrastructure and deployment services
  • constructing IT infrastructure for organizations
  • scalable, high-performance data architecture solutions
  • AI/GenAI use cases
  • AI/GenAI infrastructure