AI/ML Engineer

• AI Development & Engineering
• Design, develop, and deploy machine learning and deep learning models for real-world applications.
• Build and fine-tune large language model (LLM)-based solutions (e.g., chatbots, recommendation systems, automation tools).
• Implement end-to-end ML pipelines including data preprocessing, model training, evaluation, optimization, and deployment.
• System Architecture & Integration
• Integrate AI services into existing products using APIs, microservices, and cloud platforms.
• Develop scalable and efficient backend systems to support AI applications.
• Optimize model performance and cost efficiency for production environments.
• Data Engineering & MLOps
• Collaborate with data engineers to collect, clean, and structure datasets.
• Implement MLOps best practices for continuous integration, monitoring, and version control of models.
• Ensure security, compliance, and ethical use of data in all AI systems.
• Collaboration & Innovation
• Partner with product managers, designers, and business stakeholders to create AI-driven features.
• Stay updated on AI research trends and evaluate new tools/techniques for adoption.
• Document AI systems, decisions, and processes for internal knowledge sharing.

AI Ops

• AI Development & Engineering
• System Architecture & Integration
• Data Engineering & MLOps
• Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field.
• Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn, Transformers).
• Experience building and deploying models on cloud platforms (Azure, AWS, Google Cloud).
• Solid understanding of machine learning algorithms, deep learning architectures, and NLP.
• Hands-on experience with LLM fine-tuning, embeddings, vector databases, or RAG pipelines.
• Experience developing REST APIs, microservices, or backend components.
• Ability to work with large, complex datasets and data pipelines.
• Experience with MLOps tools: MLflow, Kubeflow, Docker, Kubernetes.
• Familiarity with GenAI frameworks: LangChain, LlamaIndex, Azure OpenAI, Hugging Face.
• Knowledge of reinforcement learning, computer vision, or multimodal AI.
• Experience with prompt engineering or model evaluation frameworks.
• Strong analytical and problem-solving abilities.
• Excellent communication skills, both technical and non-technical.
• Ability to work in a dynamic, fast-paced environment.
• Collaborative mindset with a passion for innovation.

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