What You’ll Do

As a Senior AI Engineer at [Your Company Name], you will:

• Design, build, and deploy machine learning and AI models for real-world applications.
• Collaborate with data scientists, engineers, and product teams to integrate AI-driven features into products.
• Lead end-to-end development of ML pipelines — from data preprocessing to model training, evaluation, and deployment.
• Optimize models for performance, scalability, and cost-efficiency in production environments.
• Stay ahead of emerging AI technologies (LLMs, multimodal models, vector databases, etc.) and evaluate their potential for our use cases.
• Contribute to AI architecture decisions and best practices across the engineering organization.
• Mentor junior team members and foster a culture of experimentation and technical excellence.

What We’re Looking For

• 5+ years of experience in software engineering or applied machine learning roles.
• Strong background in machine learning, deep learning, or natural language processing (NLP).
• Proficiency in Python and frameworks such as PyTorch, TensorFlow, or JAX.
• Experience deploying models in production (e.g., via AWS Sagemaker, Vertex AI, Docker, or Kubernetes).
• Solid understanding of data engineering, MLOps, and model lifecycle management.
• Strong problem-solving skills and ability to translate research into scalable production systems.
• Excellent communication skills and cross-functional collaboration experience.

Nice to Have

• Experience working with large language models (LLMs), retrieval-augmented generation (RAG), or vector databases.
• Familiarity with reinforcement learning, computer vision, or multimodal AI.
• Contributions to open-source AI projects or published research.
• Familiarity with distributed computing and GPU optimization.