AI Engineer
Job Description
Position Summary, Responsibilities and Expectations:
• Own AI/ML feature development across multiple platforms, end to end.
• Handle model integration, including choosing and swapping providers as needs change.
• Build and maintain LLM pipelines and orchestration logic.
• Set up retrieval systems and the data logic that feeds them.
• Run evaluation on model output and iterate to improve accuracy, reliability and cost.
• Optimize performance, including cost and latency trade-offs in production.
• Track emerging AI tools and frameworks and bring in what's worth adopting.
Essential Skills and Experience:
• 4+ years of software engineering experience.
• Strong Python skills.
• Production experience with LLMs.
• Experience with vector stores and retrieval-augmented generation.
• Experience with agentic frameworks.
• Practical MLOps experience, including deploying and monitoring AI systems in production.
• A working grasp of cost and latency trade-offs when running LLM-based systems at scale.
• Comfortable working alongside a small core engineering team.
• Fluent English, both in written and speaking.
• Own AI/ML feature development across multiple platforms, end to end.
• Handle model integration, including choosing and swapping providers as needs change.
• Build and maintain LLM pipelines and orchestration logic.
• Set up retrieval systems and the data logic that feeds them.
• Run evaluation on model output and iterate to improve accuracy, reliability and cost.
• Optimize performance, including cost and latency trade-offs in production.
• Track emerging AI tools and frameworks and bring in what's worth adopting.
Essential Skills and Experience:
• 4+ years of software engineering experience.
• Strong Python skills.
• Production experience with LLMs.
• Experience with vector stores and retrieval-augmented generation.
• Experience with agentic frameworks.
• Practical MLOps experience, including deploying and monitoring AI systems in production.
• A working grasp of cost and latency trade-offs when running LLM-based systems at scale.
• Comfortable working alongside a small core engineering team.
• Fluent English, both in written and speaking.
More Info
About Company
Skills:
API design, Python, embeddings, pgvector, Qdrant, vector databases, context window management, search IR techniques, LangGraph, BM25, agent RAG frameworks, OpenTelemetry, Langfuse, structured output, observability, LangChain, CrewAI, cross-encoders, tracing, LLMs, Monitoring, prompt engineering, AutoGen, rerankers, hybrid search, Milvus, Weaviate, LlamaIndex, function calling
Skills:
graph databases , Tensorflow, Pytorch, MLops, Python, LangChain, CrewAI, Agentic AI frameworks, knowledge graphs, Hugging Face, prompt engineering, LangGraph, AutoGen, RAG, SLM fine-tuning, LlamaIndex
Skills:
production deployment , Apis, Testing, Data Science, Microsoft Azure, Databricks, Python, Generative AI, data pipelines, Machine Learning Engineering, Monitoring, AI ML Engineering, software engineering principles, Large Language Models
Skills:
Retrieval-Augmented Generation (RAG) pipelines, Git, Rest Apis, Python, AI Agents, Data preprocessing, Vector Search, Generative AI solutions, AI application testing, Embeddings, CI/CD, LLM technologies, Prompt Engineering
Skills:
object detection , C++, Ip Cameras, Git, Pytorch, Opencv, Python, Computer Vision, Action Recognition, NVIDIA Jetson, TensorRT, Pose Estimation, Tracking, ONNX, Real-time AI processing systems, Video data processing