AI Engineer

Particle41 is seeking an AI Engineer to design, develop, and deploy machine-learning and deep-learning models, with a heavy focus on Generative AI. You will collaborate with data scientists and engineers to build scalable pipelines and ensure production readiness. This role involves working directly with clients to translate business requirements into sophisticated AI solutions.

Key Responsibilities

• Generative AI & Agents: Build GenAI solutions using RAG, Agentic Workflows, MCP Servers, and Conversation AI Agents.
• End-to-End ML: Lead the lifecycle from data ingestion and preprocessing to model training, evaluation, deployment, and monitoring.
• Production Deployment: Develop and integrate AI models into production systems using APIs, microservices, and cloud deployments.
• Audio AI: Implement solutions using Text-to-Speech and Speech-to-Text models like Deepgram, ElevenLabs, and Cartesia.
• Optimization: Optimize models for performance, scalability, robustness, and cost-efficiency (handling drift, bias, and fairness).

Requirements

• Experience: 3+ years of hands-on experience in AI/ML model development and deployment.
• Tech Stack: Strong programming skills in Python and experience with frameworks like TensorFlow, PyTorch, LangChain, and LangGraph.
• Modern AI Stack: Experience with Vector Databases (Pinecone, FAISS) and fine-tuning LLMs.
• Real-Time & Tools: Familiarity with LiveKit, Agents SDKs, and MCP Clients/Servers.
• MLOps: Familiarity with MLOps tools like MLflow, Kubeflow, or SageMaker.

Nice to Have

• Publications, open-source contributions, or personal projects in the AI/ML domain.
• Experience in computer vision or time-series modeling (ARIMA, Prophet).