Senior Data Scientist – Generative AI, Geotab

Senior Data Scientist - Generative AI, Geotab

Company Geotab
Job title Senior Data Scientist, Generative AI
Job location Atlanta, Georgia
Type Full Time

Responsibilities:

  • Research, develop, and implement novel Generative AI solutions tailored to telematics applications.
  • Design and develop generative AI models using advanced machine learning and deep learning techniques.
  • Implement LLM-powered solutions, employing techniques like prompt engineering and Retrieval Augmented Generation (RAG)-based systems.
  • Analyze experimental results to evaluate the effectiveness and accuracy of Generative AI algorithms.
  • Build evaluation systems to assess model output quality and product experience objectively.
  • Design architectures that meet product requirements, balancing considerations such as AI safety and latency.
  • Work with software developers, AI engineers, and stakeholders to integrate generative AI solutions into telematics platforms.
  • Provide project leadership as a subject matter expert (SME), guiding team members and participating in cross-departmental projects.
  • Mentor team members on best practices for AI product development.
  • Generate detailed reports and presentations to communicate the impact and value of generative AI solutions to stakeholders.
  • Stay updated on industry trends and advancements in generative AI and prompt engineering, integrating best practices into development cycles.
  • Engage with the AI research community, applying the latest findings and technologies to AI initiatives.
  • Implement new statistical or mathematical methodologies for data analysis models.
  • Develop algorithms and predictive models to solve complex business problems.
  • Conduct causality experiments using A/B tests or epidemiological approaches to identify root issues.
  • Extract value from big data infrastructure (e.g., Google BigQuery) through complex queries and analyses.
  • Collaborate with cross-functional teams to seamlessly integrate AI technologies into platforms, ensuring personalized user experiences.
  • Maintain comprehensive documentation of research, methodologies, model design, and experimental results.

Requirements & Skills:

  • 5-8 years in a Data Scientist or similar role. Writing SQL queries, programming in Python, and building production machine learning models.Experience with transformer models such as BERT and GPT, and pre-LLM NLP models like word2vec or GloVe.
  • Masters in Data Science, Mathematics, Computer Science, Statistics, or related field.
  • Experience with OpenAI’s and VertexAI frameworks and APIs
  • Experience in data augmentation techniques to enhance model training and performance.
  • Proven experience in developing and deploying generative AI projects in real-world applications, including fine-tuning and distilling models.
  • Expertise in prompt engineering closed-source models (e.g., GPT) or open-source models (e.g., Mixtral) for specific application needs.
  • Proficiency in model deployment and cloud services (e.g., GCP, Azure, AWS) for scalable solutions.
  • Knowledge of data management, including building datasets and evaluating model performance.
  • Familiarity with advanced AI frameworks and libraries such as PyTorch, TensorFlow, and Langchain.
  • Solid understanding of machine learning principles, statistical analysis, and predictive modeling.
  • Ability to ensure ethical considerations in Generative AI, including data privacy, bias detection, and model explainability.
  • Strong project management skills, capable of leading projects from conception to completion.
  • Excellent communication skills for effective collaboration across teams and with external partners.
  • High attention to detail and analytical skills, with the ability to make well-judged decisions.
  • Strong team player with the ability to engage effectively at all organizational levels.
  • Business acumen to align technical initiatives with strategic business objectives.
  • Adaptive mindset to stay current with evolving technologies and market demands.
  • Entrepreneurial mindset and comfort in a flat organizational structure.

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