AI Engineering Manager - SFL Scientific
- Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
- 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
- Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
- 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
- Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
- Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
- Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
- Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
- Mentor, motivate, and coach junior members on technical best practices and inspire professional development
- 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 lead projects or workstreams
- 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 mentor and provide clear guidance to others
- Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.)
- 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
- 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
- 6+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
- 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
- 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
- 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
- 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
- Live within commuting distance to one of Deloitte's consulting offices
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Limited immigration sponsorship may be available
- Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
- AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
- 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack
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