solutions. You'll work across the stack, contribute to infrastructure, and collaborate with multidisciplinary teams to deliver impactful digital experiences. Key Responsibilities Build GenAI applications using frameworks like LangChain, LangGraph, or CrewAI. Develop microservices using Python (FastAPI) or TypeScript (Express). Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic, Mistral More ❯
solutions. You'll work across the stack, contribute to infrastructure, and collaborate with multidisciplinary teams to deliver impactful digital experiences. Key Responsibilities Build GenAI applications using frameworks like LangChain, LangGraph, or CrewAI. Develop microservices using Python (FastAPI) or TypeScript (Express). Create front-end applications with React, TypeScript, and frameworks like Next.js or Vite. Integrate LLMs (e.g., OpenAI, Anthropic, Mistral More ❯
with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time). Familiarity More ❯
with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time). Familiarity More ❯
of Git/GitHub workflows and DevOps tooling Nice to have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based systems More ❯
of Git/GitHub workflows and DevOps tooling Nice to have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based systems More ❯
with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using tools like Axolotl, LoRA, or QLoRA. Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI) Experience with observability and evaluation tools for LLMs such as TruLens or Helicone. Experience with AI safety and reliability frameworks like Guardrails AI. More ❯
with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using tools like Axolotl, LoRA, or QLoRA. Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI) Experience with observability and evaluation tools for LLMs such as TruLens or Helicone. Experience with AI safety and reliability frameworks like Guardrails AI. More ❯
and market data, improving search, discoverability, and insight accuracy. LLM & Machine Learning Application Engineering Design, build, and maintain traditional ML and LLM models and pipelines. Build LLM apps using LangGraph/LangChain: tools/function calling, structured outputs (JSON Schema), agents, and multi-step reasoning. Implement ASR/TTS and multimodal where relevant (e.g., Whisper). Choose customization paths pragmatically … in Python and relevant ML/LLM libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn). Strong in Python, API design, asynchronous programming, and integration patterns. Hands-on with LangGraph/LangChain, LlamaIndex or Semantic Kernel for orchestration (tools, agents, guards, structured I/O). Familiarity with Azure OpenAI and at least one open model stack (e.g., Llama/ More ❯
and Databricks ecosystems. Apply Generative AI techniques for text, code, image, and multi-modal use cases using advanced prompt engineering. Utilize modern GenAI toolkits and libraries, including: PyTorch LangChain, LangGraph, Model Context Protocol, Google's Agent Development Kit (ADK), and similar agentic frameworks. Develop experiments for LLM fine-tuning, retrieval-augmented generation (RAG), and multi-agent AI workflows . Deliver … expertise in: Python (advanced) AI/ML libraries (PyTorch, Hugging Face, Scikit-learn, TensorFlow, optional) Prompt engineering and fine-tuning LLMs for task-specific use cases Familiarity with LangChain, LangGraph, MCP, or other agentic frameworks for building AI applications. Excellent communication and stakeholder management skills. Strong ability to connect business concepts with AI-driven architectures and KPIs. More ❯
