AI Engineer

Job Overview:

We are seeking skilled AI Engineers with 1-7 years of experience to join our dynamic and fast-growing team. In this role, you will design, develop, and deploy AI-driven solutions, leveraging cutting-edge technologies in deep learning, natural language processing (NLP), computer vision, and generative AI. This position offers a unique opportunity to work on innovative AI applications, optimize models for high performance, and integrate AI solutions into our SaaS platform.

Key Responsibilities:

AI Model Development & Deployment:

• Design, train, and fine-tune deep learning models for various applications, including image, video, and text processing.

• Optimize AI models for performance, efficiency, and scalability (e.g., using ONNX, TensorRT).

• Deploy AI models in production environments using cloud services like AWS, GCP, or Azure.

Data Processing & Engineering:

• Collect, clean, and preprocess structured and unstructured data for AI applications.

• Implement feature engineering techniques to enhance model performance.

• Work with large-scale datasets, vector embeddings, and retrieval-augmented generation (RAG).

AI Explainability & Interpretability:

• Implement explainable AI techniques to provide transparency in model decisions.

• Develop interpretable visualizations and reports to communicate AI model insights to stakeholders.

Collaboration & Research:

• Collaborate closely with data scientists, software engineers, and product teams to integrate AI seamlessly into applications.

• Stay updated with the latest AI research and trends to drive continuous innovation.

Required Skills & Qualifications:

• Educational Background: Bachelor's or Master’s degree in Computer Science, AI, Machine Learning, or a related field.

• Programming: Proficiency in Python and experience with frameworks such as TensorFlow, PyTorch, ONNX, or OpenCV.

• Machine Learning & Deep Learning: Hands-on experience with advanced models, including transformers, CNNs, RNNs, GANs, and Vision Transformers (ViTs).

• Cloud & MLOps: Experience working with cloud-based AI services like AWS SageMaker, GCP Vertex AI, or Azure AI.

• Optimization & Inference: Knowledge of model optimization techniques, such as quantization, pruning, and hardware acceleration.

• Databases & Data Processing: Experience with SQL, NoSQL, and vector databases (e.g., Pinecone, FAISS).

• NLP & Generative AI: Experience with large language models (LLMs) such as BERT, GPT, and embedding-based text understanding.

• Computer Vision: Expertise in image and video processing, object detection, and real-time inference.

• Security & Fraud Detection (Preferred): Experience in AI-based fraud detection, cybersecurity, or biometric authentication is a plus.

Preferred Skills:

• Experience in real-time multimodal analytics for cloud and edge computing.

• Understanding of legal and ethical considerations in AI.

• Familiarity with Kubernetes and Docker for AI model deployment.

• Contribution to AI open-source projects or research publications.

• Python and R programming
• GCP/AWS AI microservices (GCP VertexAI, AWS Sagemaker or AzureAI)
• Machine Learning and Deep Learning
• MLOps and AIOps experience
• TensorFlow, PyTorch
• LangGraph / LlamaIndex