AI Engineer

Responsibilities Design and develop AI systems and intelligent applications, leveraging deep learning, NLP, and computer vision. Collaborate with cross-functional teams to identify business problems solvable through AI. Build production-ready APIs that expose AI capabilities across platforms. Integrate AI solutions into mobile, web, or enterprise software stacks. Research and experiment with generative AI (LLMs, GANs), reinforcement learning, and other advanced techniques. Optimize inference performance and latency using quantization, pruning, or ONNX. Maintain AI systems through continuous evaluation, retraining, and performance tuning. Develop reusable AI components and tools that accelerate engineering velocity.

Requirements Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, or related discipline. 3-6+ years of experience delivering AI/ML models into production systems. Strong programming skills in Python and familiarity with C++, Java, or Go. Proficiency with AI/ML libraries like TensorFlow, PyTorch, Hugging Face Transformers, OpenCV. Experience building RESTful APIs and microservices that expose AI logic. Familiarity with AI model lifecycle tools like MLflow, Triton Inference Server, ONNX Runtime. Experience deploying AI solutions to cloud platforms (Azure, AWS, GCP).

Preferred

Qualifications Experience with LLMs (e.g., GPT-3/4, Claude, Mistral) and prompt engineering. Familiarity with vector databases (Pinecone, Weaviate) and RAG systems. Hands-on experience with AI infrastructure tools (NVIDIA Triton, Ray, or DeepSpeed). AI-related certifications or contributions to open-source AI projects.