Generative AI – Domain Solution Architect

This position is for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.The key responsibilities will be to prepare modern Natural Language Technology (NLT) platforms to gain insights from key business data. The employee will be responsible for designing, implementating and managing data preparation and advanced analytics tools in addition to demonstrating insights from the varied sources of data to business users. Responsibilities also include developing and designing language understanding/generation systems and effectively using text representation techniques. Objectvies of the role: Work in tandem with our engineering partners to identify and implement the most optimal cloud-based ML solutions for the company. Research, design and adopt cutting-edge NLG algorithms to address real-world challenges such as summarisation. Define and document best practices and strategies regarding deployment and infrastructure maintenance. Ensure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design. Maintain a platform that automates creating, training, deploying and updating machine learning models. Managing BI Platforms in accordance with company security guidelines Basic Requirements: 8-12 years of production model deployment experience for AI/ML solutions. Designing, developing, and researching Machine Learning systems, models, and schemes through data science and data analytics prototypes. Understanding of Natural Language Processing(NLP), Natural Language Understanding(NLU) and Natural Language Generation(NLG). Develop and implement technical efforts to design, build, and deploy AWS ML models , including large-scale data processing, computationally intensive statistical modeling, and advanced analytics. Familiarity with deep learning, machine learning and NLP/NLG frameworks(like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries like scikit-learn, spacy, gensim, CoreNLP etc. Should have experience in AWS services such as SageMaker, Elasticsearch, EC2, and general knowledge of AWS architecture & other services. Ability to write robust code in Python, Java and R. Experience optimizing model hyperparameter tuning for speed and cost Experience in building MLOps pipeline using MLOps frameworks like Kubeflow, MLFlow, and DataRobot. Experience with Docker and Kubernetes. Familiarity with Eventbridge and AWS step function for workload orchestration. Experience with Agile Development. Good experience in process improvement/change management methods. Knowledge of various aspects of an enterprise technology architecture like business, information, data, network, and security. Understanding and knowledge of system development life cycle methodologies (such as waterfall, agile software development, rapid prototyping, and DevOps). Understanding and knowledge of IT service management (ITSM) and Information Technology Infrastructure Library (ITIL). Excellent analytical, planning, organizational and technical and skills. Skilled at influencing, guiding, and facilitating stakeholders and peers with decision making. Ability to articulate new ideas and concepts to technical and nontechnical audiences.

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