AI Software Engineer for Remote Team

We're looking for an experienced AI Software Engineer to design, build, and deploy machine learning and applied AI features. You'll take ideas from prototype to production and work closely with our team to ship features that real users depend on. What you'll do: - Design and build ML and LLM-powered features such as RAG search, document classification, recommendations, chat assistants. - Develop data pipelines for training, evaluation, and inference - Integrate LLM APIs (OpenAI, Anthropic, open-source models) and fine-tune or adapt models where needed - Build evaluation frameworks to measure model quality, latency, and cost - Deploy and monitor models in production via APIs, containers, and cloud services - Write clean, tested, documented code and explain trade-offs clearly What we're looking for: - 4+ years of software engineering experience, including 2+ years shipping ML/AI to production - Strong Python skills and experience with PyTorch or TensorFlow - Hands-on experience with LLMs, embeddings, vector databases, and retrieval-augmented generation (RAG) - Experience with cloud platforms (AWS, GCP, or Azure) and Docker - Solid understanding of ML fundamentals: model selection, evaluation, overfitting, data quality - Clear written communication in English and comfort working asynchronously Nice to have: - MLOps tooling (MLflow, Weights & Biases, Kubeflow) - Experience with agent frameworks (LangChain, LlamaIndex) or custom agent workflows - Backend experience (FastAPI, Node.js) and SQL/NoSQL databases We're looking for an experienced AI Software Engineer to design, build, and deploy machine learning and applied AI features. You'll take ideas from prototype to production and work closely with our team to ship features that real users depend on. What you'll do: - Design and build ML and LLM-powered features such as RAG search, document classification, recommendations, chat assistants. - Develop data pipelines for training, evaluation, and inference - Integrate LLM APIs (OpenAI, Anthropic, open-source models) and fine-tune or adapt models where needed - Build evaluation frameworks to measure model quality, latency, and cost - Deploy and monitor models in production via APIs, containers, and cloud services - Write clean, tested, documented code and explain trade-offs clearly What we're looking for: - 4+ years of software engineering experience, including 2+ years shipping ML/AI to production - Strong Python skills and experience with PyTorch or TensorFlow - Hands-on experience with LLMs, embeddings, vector databases, and retrieval-augmented generation (RAG) - Experience with cloud platforms (AWS, GCP, or Azure) and Docker - Solid understanding of ML fundamentals: model selection, evaluation, overfitting, data quality - Clear written communication in English and comfort working asynchronously Nice to have: - MLOps tooling (MLflow, Weights & Biases, Kubeflow) - Experience with agent frameworks (LangChain, LlamaIndex) or custom agent workflows - Backend experience (FastAPI, Node.js) and SQL/NoSQL databases