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This role will focus on developing and optimizing AI workloads, particularly around hardware AI acceleration, to enable efficient processing and advanced use cases. Additionally, you will engage with research teams to share insights, refine AI models, and explore the feasibility of various AI techniques for solving complex problems.
- Collaborate with the Customer Account Executive, Sales Specialist, and Solution Architect to uncover and address challenges or obstacles in both new and existing customer accounts.
- Design, plan, and implement AI systems for customers, with the ability to develop data pipelines, machine learning (ML) pipelines, and approaches for training and serving ML models, leveraging additional support and resources as needed.
- Lead technical deep dives, proofs of concept, internal sprints and the development of industry-specific AI solutions to enhance adoption and customer success.
- Identify key AI stakeholders within customer organizations, advocating for their needs within both business and technical teams.
- Collaborate closely with internal AI business units and engineering teams, offering valuable market feedback on products and solutions.
- Participate in customer advocacy, including speaking at conferences, writing blog posts, and other public-facing activities.
Solution Engineer with over 5 years of practical experience in the following areas:
Use Case Development, including building AI applications such as deep learning, LLM/RAG, NLP, computer vision, and pattern recognition.
Technical Expertise in AI Frameworks and Tools: Expertise with various machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and cloud AI services to design and deploy production-ready AI systems.
Machine Learning Operations Design, including hands-on experience in AI systems architecture, with the ability to design and explain data and ML pipelines, as well as training and serving approaches.
Experience with CI/CD and MLOps practices, including automation via Infrastructure as Code (IaC) tools such as Ansible, in the context of ML and LLM operations.
Proven ability to deliver technical presentations and lead business value discussions.
Customer-Centric Mindset: A passion for delivering exceptional customer experiences, ensuring that AI solutions meet the specific needs and goals of the customer organization. Strong executive presence and public speaking skills.
Continuous Learning & Improvement: Stay up-to-date on emerging AI technologies, frameworks, and methodologies. Actively participate in internal knowledge sharing and contribute to the development of best practices and new tools.