AI Data Specialist

AI Data Specialist at Deloitte in Boise, Idaho, United States Job Description The Human Capital Offering Portfolio focuses on helping organizations manage and sustain their performance through their most important asset: their people. To stay in front, organizations need to have real-time access to Human Capital insights, experts and innovative technology solutions that are designed to not only drive but sustain and extend organizational performance and engagement. Supporting the products and capabilities of the Human Capital Offering Portfolio, our Engineering team is full of passionate, energetic, and multi-talented engineers who are excited about building the world's greatest personalized and business friendly applications. Recently building AI capabilities in all of our existing assets and building new AI enabled assets. Human Capital As-A-Service Today's disruptive environment calls for a different mindset and a new approach to drive organizational performance and enhance human capital development now and in the future. Deloitte Human Capital as a Service brings that insight, through broad and deep capabilities to help our clients optimize people, process, and technology to thrive in an unpredictable world. Recruiting for this role ends on 12/31/2024. The AI Data Specialist in Deloitte's Human Capital Consulting Asset Shop will lead the design, development, and deployment of innovative AI solutions to help clients leverage the power of artificial intelligence across their business processes. You will work closely with cross-functional teams including data scientists, engineers, and business consultants to design scalable AI architectures and integrate advanced machine learning models into business strategies. Your role is crucial in driving the adoption of AI technologies to transform client business models and deliver cutting-edge solutions. This role requires a deep understanding of Machine Learning, Statistics, Data Science, Generative AI, Large Language Models (LLMs), and Multimodal models. Additionally, the AI Data Specialist will help with recommendations for AI solution teams, focusing on modifying existing products and creating new ones. The ideal candidate will be passionate about designing, building, implementing, and maintaining industrial AI/ML/Generative AI applications. Leadership skills are essential to implement the latest AI techniques and to continuously improve the AI/ML development, delivery, and operations process. The role involves adhering to best practices from Software Engineering, DevOps, MLOps, and LLMOps. The AI Data Specialist will also help with translating project requirements into strategic solutions, ensuring the integration of cloud-native tools from major hyperscalers and machine learning to create chatbots, optimizations, and cognitive services. This role requires a blend of technical expertise and the ability to bridge the gap between intricate business challenges and transformative AI solutions. Work you'll do: Strategic Alignment and Vision + Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts. + Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases Architectural Design + Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems. Design and Technology Selection + Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools. + Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models. Research and Development + Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost. + Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions. Collaboration and Stakeholder Engagement + Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design. + Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements. Consulting & Advisory + Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices. Operational Excellence and Continuous Improvement + Be responsible for the successful execution of AI-powered applications using agile methodology. + Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms. + Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements. Risk Management and Ethical Considerations + Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations. + Address potential issues such as training data poisoning, AI model theft, and adversarial samples. Product Strategy and Business Understanding + Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products. + Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches. Tool Development and Data Management + Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization. + Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure. Required Qualifications: + Bachelor's Degree in any of Computer Science, Statistics, Data Science or a related field. + 6+ years of related consulting experience leading a team (both onshore and offshore). + 6+ years of experience gathering non-functional requirements, performing designed and validated application architecture frameworks, and executing functional and testing assignments. + 5+ years of experience working in an AI environment. + 5+ years of experience translating requirements into client ready design documents. + 5+ years of experience with application architecture analysis, design, and delivery + 5+ years of full system development life cycle implementations + Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve. + Limited immigration sponsorship may be available. Preferred Qualifications: + Advanced degrees such as Masters or PhD are preferred + Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect + 5 + years of experience in Data Science, Statistics, and Machine Learning + 5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing + 5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment + 5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Mi To view full details and how to apply, please login or create a Job Seeker account