Design, develop, and deploy AI/ML models and Generative AI solutions (LLMs, multi-modal models, embeddings, RAG pipelines, prompt engineering, and fine-tuning)
Build AI-powered applications that integrate into business workflows (copilots, intelligent assistants, automation systems)
Evaluate, prototype, and productionize state-of-the-art AI frameworks and foundation models (open-source and proprietary)
Optimize model performance, scalability, and latency in cloud and enterprise environments (Azure, AWS, GCP)
Collaborate with cross-functional stakeholders to translate business problems into AI-driven solutions
Implement MLOps practices for reliable model training, deployment, monitoring, and lifecycle management
Ensure responsible AI practices, including fairness, transparency, security, and compliance
Requirements
Bachelor’s or Master’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field (PhD a plus)
5+ years of experience in AI/ML engineering, with a strong track record of building production-grade AI applications
Proficiency in Python
Familiarity with modern AI/ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex)
Deep knowledge of Generative AI techniques: prompt engineering, fine-tuning, embeddings, vector databases, and retrieval-augmented generation (RAG)
Hands-on experience with cloud-based AI services and architectures (Azure OpenAI, AWS Bedrock, GCP Vertex AI)
Strong understanding of MLOps, APIs, microservices, and containerization (Docker, Kubernetes)
Excellent problem-solving, collaboration, and communication skills
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