AIML Architect WITH MLOPS Experience
2 days ago
We are seeking a highly experienced and technically proficient AI/ML Architect to lead the design and implementation of advanced machine learning systems across enterprise platforms. This is an individual contributor role focused on delivering high-impact solutions in the areas of Generative AI, large language models (LLMs), conversational AI, and scalable ML architectures.
As an AI/ML Architect, you will bring deep expertise in model development, system design, and deployment strategies. You will work closely with cross-functional teams to define and implement AI-driven solutions that are both technically sound and aligned with business goals.
Key Responsibilities:
- Architect end-to-end AI/ML solutions using deep learning, NLP/NLU, LLMs, and multimodal models.
- Design and build scalable, production-grade ML systems integrated with backend services, APIs, and enterprise data platforms.
- Evaluate, fine-tune, and deploy large-scale LLMs and Generative AI models for various enterprise use cases.
- Lead technical design and hands-on development of ML pipelines and inference services.
- Collaborate with engineering, data science, and product teams to identify opportunities for AI automation and optimization.
- Troubleshoot model and system performance issues in distributed environments.
- Contribute to the development and enforcement of ML best practices, model governance, and technical standards.
- Present complex ML concepts and technical insights clearly to both technical and non-technical stakeholders.
Required Qualifications:
- 14+ years of experience in designing, building, and deploying AI/ML systems in enterprise environments.
- Strong foundation in machine learning, deep learning, and statistical modeling.
- Proven experience with Generative AI and large language models (text and multimodal).
- Hands-on expertise in Python and ML/NLP frameworks such as PyTorch, TensorFlow, Hugging Face, NumPy, and Pandas.
- Deep experience in natural language processing (NLP), natural language understanding (NLU), and conversational AI systems.
- Demonstrated ability to integrate ML models into scalable backend systems via APIs and data connectors.
- Excellent problem-solving skills, especially in distributed and large-scale system contexts.
- Strong communication and documentation skills; able to work independently as a technical leader within projects.
Preferred Qualifications:
- Experience with MLOps frameworks (e.g., MLflow, Airflow, Kubeflow) and model lifecycle management.
- Knowledge of responsible AI practices, model interpretability, and ethical considerations.
- Experience working with hybrid cloud/on-prem deployment models.
- Familiarity with multimodal AI (e.g., text + image, vision-language models).
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