Gen AI architect - India
- Infosys
- 5 - 10 years
- Ahmedabad
- 2 days ago
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Job Description
Job Title
Gen AI Senior Lead
No of years Experience (Developer/lead)
- More than 9 Years of IT industry experience in which 5/6 years should be in AI/ML/DS domain, including Gen AI technologies.
Technology
- Gen AI Technologies: Prompt Engineering, LLM Development using Langchain. Semantic Kernel , Open Source/ API based LLMs
- AIML Subfields such as Neural Networks, Computer Vision, Speech Processing, Natural Language Processing.
- AIML Tools such as AzureML, Google ML, AWS AI/ML, H2O, DataBricks, DataRobots and any other tools
- Good understanding of various Generative AI techniques, including GANs, VAEs, and other relevant architectures.
- Proven experience in applying these techniques to real-world problems for tasks such as image and text generation. Conversant with Gen AI development tools like Prompt engineering, Langchain, Semantic Kernels, Function calling.
- Exposure to both API based and opens source LLMs based solution design
Key Skills
- 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.
- 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.
Roles and Responsibilities
- Client Interaction: Collaborate with client business teams to elicit project requirements and comprehend the desired outcomes. Translate client needs into technical requirements and AI solution designs.
- Solution Design: Create comprehensive AI solution designs that address client objectives. Define the architecture, model selection, and data requirements to ensure successful project execution.
- Metrics Definition: Work closely with clients to define and agree upon measurable metrics that align with business goals. Ensure that the AI solution's performance is evaluated against these metrics.
- Technical Implementation: Provide guidance to internal teams on implementing the defined AI solution. Collaborate with data scientists and engineers to integrate the solution effectively.
- Performance Monitoring: Establish mechanisms to monitor and assess the performance of deployed AI models. Make recommendations for improvements based on observed outcomes.
- Client Collaboration: Act as a liaison between the client and internal teams, maintaining effective communication throughout the project lifecycle. Provide regular updates and address any concerns or queries from clients.
- Knowledge Sharing: Stay up-to-date with the latest developments in Generative AI and related technologies. Share insights with clients and internal teams to enhance solution designs and approaches.
- Documentation: Prepare detailed documentation of solution designs, technical specifications, and project progress. Ensure that documentation is clear, concise, and accessible to relevant stakeholders.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full timeContact Details:
Company: InfosysLocation(s): Ahmedabad+ View Contact
Keyskills: Python Development gen AI Natural Language Processing Computer Vision Machine Learning
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