Senior Data Scientist - Generative Ai

DENTSU CREATIVE is dentsu's global creative network that transforms brands and businesses through the power of Modern Creativity. Widely reputed for its innovative and creative approach to marketing and advertising. Dentsu Creative has won numerous awards for its work, including Cannes Lions agency of the year 2022, D&AD Awards, and Effie Awards, among others. The company's global network of offices allows it to serve clients across industries and geographies, and it has worked with many of the world's leading brands. With its focus on creativity, innovation, and results, Dentsu Creative is a leading player in the advertising and marketing industry.

• Collaborate with client teams and stakeholders to understand their requirements and devise Gen AI models to meet these needs.
• Design, develop, and deploy custom ML models for Gen-AI solutions
• Implement MLOps to automate the deployment, monitoring, and maintenance of ML models.
• Hands-on coding to develop AI / ML solutions from scratch
• Build end-to-end data pipelines to manage data collection, extraction, pre-processing, cleansing, transformation, processing, and use inside custom built Gen-AI models
• Stay informed about the latest advancements in Gen AI, machine learning, and AI technologies to optimize our technical stack.
• Have solid knowledge and exposure across Enterprise Gen-AI Platforms and Solutions, as well as Third-party SaaS and Open Source tech leaders / providers in the Gen-AI space
• Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring.
• Lead R&D initiatives involving Gen-AI Platforms and Services, Large Language Models and existing generative AI systems

• 8+ years of overall experience in technology.
• Minimum 5+ years of overall experience in AL and ML solutions development.
• Bachelors degree in computer science, AI, Machine Learning, or related field.
• Solid understanding of Generative AI, Machine Learning, and Deep Learning algorithms, Software engineering principles
• Super hands-on with ML programming languages such as Python
• Experience with related machine learning platforms, libraries and frameworks like PyTorch, PySpark, TensorFlow, Keras, or similar with CUDA
• Experience with natural language processing (NLP) patterns such as Text representation, Embeddings, Language Modelling, and Semantic understanding
• Experience with libraries such as SpaCy, NLTK, or Stanford CoreNLP
• Experience with large language models such as GPT-4, Google PalM-2, and nVidia NeMO.
• Experience with Vector Databases for custom data and retrieval
• Strong Proficiency in AI Orchestration frameworks such as Langchain and/or Microsoft Semantic Kernel
• Prompt Engineering for implementing large language models
• Strong Proficiency in at least 1 major Cloud AI Platform / Service, and all of their primary AI services and solutions, across Azure, AWS, and Google Cloud.
• Strong Proficiency in working with an AI Cloud Service such as Azure Machine Learning, AWS Sagemaker, or Google Vertex-AI
• Strong Proficiency in being able to code and deploy custom AI / ML models on top of AI Cloud platforms such as Azure OpenAI, AWS Sagemaker/Bedrock
• Experience with and exposure to nVidia AI Cloud Foundation Service, nVidia NeMo LLM frameworks, nVidia Picasso, and other nVidia services / solutions, highly desirable
• Exceptional problem-solving skills and an innovative mindset.

• Should have deep hands-on experience with large language models (LLMs) and other generative AI techniques.
• Responsible for fine-tuning existing Foundation Models, and adapting existing base ML models.
• More importantly, you will also be responsible for coding, training, evaluating, and deploying net-new custom ML models using large datasets, helping create custom AI models for specific use cases, for different dentsu clients and brands.
• Must have deep experience of developing and implementing cutting-edge generative AI models and algorithms using state-of-the-art techniques such as GPT, VAE, and GANs.
• Must have deep technical experience working with technologies related to multimodal AI, covering text, media, image, video, audio and speech.
• Optimizing existing models for improved performance, scalability, and efficiency.
• Hands-on development in Python and PyTorch, across a variety of AI / ML frameworks, AI Cloud Services, and Gen-AI platforms, including enterprise Gen-AI tech, open-source Gen-AI tech and SaaS Gen-AI tech.