AI/Machine Learning Subject Matter Expert

at  Intone Networks

AI/Machine Learning Subject Matter Expert About the job Basic Qualifications: • Minimum of 5 years of experience in AI/ML, with a focus on generative models. • Proven track record of successfully implementing GenAI projects in real-world settings. • Experience in managing the end-to-end lifecycle of GenAI projects, from conception to deployment. • Proficiency in programming languages such as Python and other AI frameworks. • Strong analytical and problem-solving skills, with the ability to think critically and creatively. • Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. • Proven leadership abilities, with experience managing and mentoring technical teams. • Ability to work in a fast-paced, dynamic environment and adapt to changing project requirements. • Experience with cloud platforms such as AWS. • Experience in optimizing vector queries. • Proficiency in SQL. • Familiarity with natural language processing (NLP) concepts. • 1+ years of experience architecting high-impact GenAI solutions for diverse projects. • 10+ years of experience participating in projects that focused on one or more of the following areas: Predictive Analytics, Data Design, Generative AI, AI/ML, ML Ops. • 3+ years of experience using Python. Preferred Skills: • Experience with deploying and managing AI models at scale. • Demonstrates sound judgment with minimal support from practice executives through structured problem identification, mitigation, and resolution. • Exhibits strong teamwork, consistently performing as a dependable team member with an excellent work ethic. • Maintains a flexible “can-do” attitude and a commitment to success. • Professional verbal and written communication. • Undergraduate or Graduate degree preferred. Responsibility: • Develop and design scalable and efficient GenAI solutions tailored to our requirements. • Lead the implementation of GenAI systems, ensuring they are robust, secure, and performant. • Work closely with cross-functional teams, including engineers and product managers, to integrate AI solutions into existing systems. • Stay up-to-date with the latest advancements in AI and apply this knowledge to drive innovation within the company. • Create comprehensive documentation for AI solutions, including design specifications, implementation guides, and user manuals. • Provide training and mentorship to junior team members and clients on GenAI technologies and best practices. • Possess a deep understanding of cloud systems and various services available in cloud systems. • Experience working on all aspects of enterprise-scale implementation for AI/GenAI solutions, including architecture, design, security, infrastructure, MLOps/GenAIOps. • Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc. • Deep knowledge in statistics and Machine Learning models, deep learning models, NLP, Generative Adversarial Networks (GAN), and other generative models. • Experience working with RAG technologies and LLM frameworks, LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases. • Employ technical knowledge and hands-on experience with Anthropic Claude, Llama models, and other AWS LLM foundational models, BERT, Transformers, etc. • Have problem-solving abilities combined with good communication skills. • Deploy knowledge of AWS DevOps, YAML, Shell scripting, Terraform, and pipelines. • Understand how to fine-tune models, quantize models, and deploy models. • Design integrations between various cloud-based services through APIs, keeping modular designs in mind. • Apply knowledge of data engineering tools and technologies and understanding of concepts such as big data and data pipelines. • Scope, manage, and drive complex GenAI projects and programs to successful completion. • Design and implement GenAI frameworks and patterns tailored to specific needs. • Architect and lead the implementation of GenAI use cases, projects, and POCs. • Work on RAG models and Agents Frameworks to enhance GenAI solutions by incorporating relevant information retrieval mechanisms and frameworks. • Utilize best practices and creativity to address challenges and deliver impactful solutions. • Conduct market research, formulate perspectives, and communicate insights to stakeholders. • Establish strong client relationships, gaining insights into project requirements and challenges. • Communicate complex technical concepts clearly to non-technical audiences. • Handle data sets of varying complexity, processing massive data streams in distributed computing environments. • Apply business acumen to analyze data, develop insightful reports, and solve problems. • Perform ad hoc analyses based on evolving business needs. • Participate in the analysis and resolution of issues related to information flow and data content. • Collaborate with data stakeholders to address challenges and enhance data quality. • Mentor junior data scientists and GenAI engineers, fostering professional growth within the team. • Conduct training sessions to enhance overall skills within the organization

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