AI/ML Architect
2 weeks ago
About the job :
Position : AI/ML Architect(Responsible AI)
Exp : 6-8 Years
Educational Qualification : Bachelor's/Master's degree in computer science or a related field
Mandatory Requirement : Passionate about Privacy & Responsible AI
Requirements :
- Bachelor's degree or higher in an engineering field (e.g.Computer Science) with at least 6 to 8 years of relevant experience building highly scalable distributed systems.
- Proficient in programming languages like Python or C++.
- An understanding of data structures, data modeling, and software architecture.
- Deep understanding of AI, machine learning algorithms, and Gen AI applications, and AI/ML architecture with large scale scalable solutions.
- Should have experience with Statistical Modeling and Language Modeling like transformer based architecture, LSTM, Neural Network, Model Ensembling.
- Relevant experience of working with data engineers and understanding of data-stores to accomplish the data requirements for the AI/ML project.
- Good understanding of MLOps, LLMOps, Model Version Control, and Data Version Control.
- Should have hands-on experience in system design and microservice architecture.
- Specializes in at least one of the AI/ML stack, Frameworks, and tools like Pytorch and TensorFlow.
- Experience with a public cloud (AWS, Microsoft Azure, Google Cloud) and on-premise setup.
- Relevant experience that showcases practical understanding of LLMs, Prompting, Fine tuning, Vector DBs, Knowledge graph, Architectural Design for Information Retrieval using RAG.
- Experience in delivering AI/ML in customer environments.
- Excellent problem-solving skills and the ability to think strategically and analytically.
- Ability to work in a fast-paced, dynamic environment and manage multiple products simultaneously.
- Strong leadership and communication skills to effectively collaborate with various teams.
Responsibility :
- ML architect is responsible for designing end-to-end machine learning solutions that meets privacy & responsible AI business opportunities.
- Hands-on experience in MLOps/ LLMOps including data collection, data preparation, model training/ refinement, model validation, drift management and model serving.
- Deal with the dynamic work culture, scoping and sequencing the complex problems into smaller critical experiments/tasks to drive the desired outcomes.
- Collaborate with cross-functional teams to define project goals, research requirements, and develop innovative solutions.
- Write efficient and maintainable code in languages most suited to the AI/ML tasks.
- Defines best practices and architecture with deep domain knowledge.
- Constantly evolve the platform to identify bottlenecks in both runtime and development time aspects of the platform and improve them.
- Deploy ML models to production, design evaluation, monitoring plans and monitor AI/ML models in production for performance and drift.
- Work in evaluating, building and fine tuning different ML models, and LLMs to solve the problem.
- Work with broader teams of developers and architects to integrate the AI capabilities for solving the end customer problems in a secure and compliant way.
- Practice domain-compliant, secure, and responsible AI.
- Mentor team members and enable technical decision-making.
- Collaborate with product managers, customers, and other stakeholders.
- Help design and implement functional and nonfunctional requirements
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