AIML Engineer Freelance

Location: [Remote]

Job Type: [Part Time/Contract/Freelance]

Experience: 10+ Years

We are seeking a highly skilled Artificial Intelligence Engineer with deep hands-on expertise in AI/ML, deep learning, and advanced AI architectures. The ideal candidate will have extensive experience in designing, developing, and deploying AI-driven solutions using cutting-edge technologies. You will work with large-scale datasets, optimize AI models, and integrate AI into real-world applications across various industries.

• Architect, design, and implement AI-driven solutions for complex real-world problems.
• Develop and optimize machine learning (ML) and deep learning (DL) models for NLP, Computer Vision, Speech Processing, and Generative AI applications.
• Build, train, fine-tune, and deploy transformer-based models (BERT, GPT, LLaMA, Stable Diffusion, etc.).
• Work with large-scale datasets, ensuring high-quality preprocessing, feature engineering, and model optimization.
• Utilize cloud AI services (AWS SageMaker, Azure ML, GCP Vertex AI) for model deployment and scalability.
• Develop high-performance deep learning pipelines leveraging PyTorch, TensorFlow, JAX, ONNX, and Hugging Face frameworks.
• Optimize AI models using quantization, pruning, and distillation techniques for efficiency and deployment on edge devices.
• Implement and optimize MLOps pipelines for model lifecycle management, CI/CD, monitoring, and retraining.
• Develop AI solutions with LLMs (Large Language Models), Generative AI, and Reinforcement Learning (RL).
• Ensure AI models comply with ethical AI principles, security policies, and regulatory frameworks.

✅ 10+ years of hands-on experience in AI, ML, and Deep Learning.

✅ Expert in Machine Learning & Deep Learning frameworks: PyTorch, TensorFlow, JAX, ONNX.

✅ Strong experience in Large Language Models (LLMs) and Generative AI: OpenAI GPT, BERT, T5, DALL·E, etc.

✅ Advanced knowledge of Neural Networks, CNNs, RNNs, GANs, Autoencoders, and Attention Mechanisms.

✅ Experience in Natural Language Processing (NLP), Computer Vision (CV), and Reinforcement Learning (RL).

✅ Expertise in Model Optimization Techniques: Quantization, Pruning, Knowledge Distillation.

✅ Proficiency in AI-based Data Engineering: Feature extraction, dimensionality reduction, and anomaly detection.

✅ Experience with cloud-based AI services: AWS SageMaker, Azure ML, GCP Vertex AI.

✅ Strong programming skills in Python (NumPy, Pandas, Scikit-learn, FastAPI, Flask) and C++ (optional).

✅ Hands-on experience with AI Infrastructure & Deployment: Kubernetes, Docker, TensorRT, MLflow, Kubeflow.

✅ Deep understanding of vector databases and embedding models (FAISS, Pinecone, ChromaDB).

✅ Proven experience in AI security & ethical AI compliance.

• Batcheler's/ Master's in AI, Machine Learning, Computer Science, Data Science, or related fields.
• Experience in Edge AI, Federated Learning, and AI model compression.
• Knowledge of Multi-Agent AI Systems, Swarm Intelligence, and AI Governance.