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AI/ML Data Engineering Lead (Speciali...

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AI/ML Data Engineering Lead (Specialist Master) - SFL Scientific

Deloitte New York, NY (Onsite) Full-Time
Derived Salary: $151800 - $253000/Year

AI/ML Data Engineering Lead (Specialist Master) - SFL Scientific


SFL Scientific, a Deloitte Business, practice brings together several key capabilities to architect integrated programs that transform our clients' businesses, including Strategic Growth Transformation, Transformation Strategy & Design, Technology Strategy & Business Transformation, and AI & Data Strategy.


Professionals will serve as trusted advisors to our clients, working with them to make clear data engineering and architecture choices about where to play and how to win - ultimately driving growth and enterprise value.


We are hiring an AI/ML Data Engineering Lead to support the design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy and other sectors.


Recruiting for this role will end 11/30/2024.


Work You'll Do


As a Data Engineering Lead, you will lead client engagements around the design and delivery of innovative solutions for complex, R&D-type problems. You will be responsible for the technical direction and solutions architecture, while engaging with internal stakeholders, understanding business priorities, defining the data strategy, and leading application deployment in order to solve our clients' use cases. You will work cross-functionally with data scientists, project managers, and industry experts to develop robust data platforms and cloud solutions.


In our consultative approach, we are platform agnostic and are committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, MLOps, data engineering and streamlining IT infrastructure processes. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community.


  • Work with clients to design, develop, and deploy new architectures for machine learning & automation applications such as ELT functions, HPC/compute infrastructure, hybrid cloud solutions, database management, and optimization of DevOps procedures




  • 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 DB, 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 the technical best practices and inspire professional development




The Team


SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.


Basic Qualifications:


  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience




  • 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 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




Preferred Qualifications:


  • 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)




  • Expert with GPU computing (CUDA, OpenCL) and HPC system software stack




  • Excellent verbal and written communication skills and experience in a client-facing or team management role




Information for applicants with a need for accommodation:

Recommended Skills

  • Agile Methodology
  • Algorithms
  • Ansible
  • Apache Kafka
  • Architecture
  • Artificial Intelligence

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