AI/ML/GenAI ArchitectACL Digital • Karnataka, India

AI / ML / GenAI Architect

ACL Digital • Karnataka, India

30+ days ago

Job description

10+ years of progressive experience in designing and implementing enterprise-grade AI / ML solutions.

Minimum of 3 successful end-to-end project implementations of AI / ML / GenAI solutions in production environments, demonstrating strong business impact and scalability.

Deep expertise in Generative AI architectures, including but not limited to :

Large Language Models (LLMs) - prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, prompt chaining, agentic workflows.

Generative Adversative Networks (GANs), Variational Autoencoders (VAEs), Diffusion Models, etc.

Experience with various LLM frameworks / libraries (e.g., LangChain, LlamaIndex).

Proven experience with leading cloud AI platforms (at least one of the following) :

AWS : SageMaker, Comprehend, Textract, Polly, Bedrock, etc.

Azure : Azure Machine Learning, Azure OpenAI Service, Cognitive Services.

GCP : Vertex AI, Google Cloud AI Platform, Google Cloud Vision / Natural Language AI.

Strong understanding of core Machine Learning concepts and algorithms : Supervised, Unsupervised, Reinforcement Learning, Deep Learning.

Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn, Hugging Face Transformers).

Experience with MLOps principles and tools : CI / CD for ML, model versioning, monitoring, deployment, drift detection (e.g., MLflow, Kubeflow, Sagemaker MLOps services, Azure ML pipelines).

Solid understanding of data engineering principles relevant to AI / ML workloads (data pipelines, ETL / ELT, data governance, feature stores).

Strong knowledge of distributed computing frameworks (e.g., Spark, Dask) for large-scale data processing.

Exceptional communication skills (written and verbal) : Ability to articulate complex technical concepts to both technical and non-technical stakeholders, conduct compelling presentations, and influence decision-making.

Demonstrated experience in leading architectural design discussions and making critical technical decisions.

Problem-solving mindset with the ability to troubleshoot and resolve complex technical issues in production.

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