Role & responsibilities

Technical Proficiency: An overall understanding of below technologies is required :

Machine learning algorithms: Linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks

Data science tools: NumPy, SciPy, Pandas, Matplotlib,

TensorFlow, Keras

Cloud computing platforms: AWS, Azure, GCP

Natural language processing (NLP): Transformer models,

attention mechanisms, word embeddings

Computer vision: Convolutional neural networks, recurrent neural networks, object detection

Robotics: Reinforcement learning, motion planning, control systems

Data ethics: Bias in machine learning, fairness in algorithms

Responsible AI: Should have proficient knowledge in

Responsible AI and Data Privacy principles to ensure ethical data handling, transparency, and accountability in all stages of AI development. Must demonstrate a commitment to upholding privacy standards, mitigating bias, and fostering trust within data-driven initiatives.

Solution Design: Ability to design end-to-end AI solutions,

from requirement elicitation and model selection to deployment strategy.



Experience in crafting architectures that encompass data preprocessing, model integration, and performance optimization.

Communication Skills: Excellent verbal and written communication skills to engage with clients, articulate technical concepts to non-technical stakeholders, and work collaboratively with cross-functional teams.

Secondary Skill Set

Domain Knowledge: Familiarity with the industry domains in which the AI solutions will be applied. This includes understanding the specific challenges and requirements of different sectors such as healthcare, finance, or manufacturing.

AI & Automation Services

Project Management: Basic project management skills to oversee project timelines, milestones, and deliverables.

Experience in coordinating with internal teams and clients to ensure project success.

Data Understanding: A foundational grasp of data preprocessing, feature engineering, and data quality assurance processes. This aids in understanding the data requirements of AI models.

📌 Hiring For Geberative AI Lead/Architect (Bengaluru)
🏢 Glauben Technologies
📍 Bengaluru