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
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 & Analytics - OtherRole: Data Science & Analytics - OtherEmployement Type: Full time