AI Platform Engineer / AI Infrastructure Engineer

Join to apply for the AI Platform Engineer / AI Infrastructure Engineer role at Axiomatic_AI

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About us

Axiomatic_AI is dedicated to accelerating R&D by developing the next generation of Automated Interpretable Reasoning, a verifiably truthful AI model built for reasoning in science and engineering. We empower engineers in hardware design and Electronic Design Automation (EDA), with a mission to revolutionize the fields of hardware design and simulation in the photonics and semiconductor industry.

Position Overview

As an AI Platform Engineer, you will bridge AI research and production software, building and maintaining AI infrastructure, enabling developers to deploy work safely, and designing APIs for AI inference, prompt management, and evaluation. You will also implement MLOps pipelines, optimize performance, and collaborate closely with backend engineers.

Key Responsibilities

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• Build and maintain AI infrastructure: model serving, vector databases, embedding pipelines.
  
• Enable AI developers to deploy reproducibly and safely.
  
• Design APIs for AI inference, prompt management, and evaluation.
  
• Implement MLOps pipelines: versioning, monitoring, logging, experimentation tracking.
  
• Optimize performance: latency, cost, throughput, and reliability.
  
• Collaborate with backend engineers to integrate AI capabilities.
  
• Monitor model performance, drift, and set up logging and observability.
  
• Build CI/CD pipelines for model deployment.
  
• Document AI infrastructure and best practices.
  
• Mentor AI developers on software practices.
  

Required Skills & Experience

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• 7+ years of software engineering experience (Python preferred).
  
• Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar.
  
• Knowledge of vector databases: Pinecone, Chroma, Weaviate, FAISS.
  
• Cloud infrastructure experience: GCP (Vertex AI preferred) or AWS (SageMaker).
  
• API development: FastAPI, REST, async programming.
  
• CI/CD and DevOps: Docker, Terraform, GitHub Actions.
  
• Monitoring and observability.
  
• Problem‑solving mindset; comfortable debugging complex distributed systems.
  
• Experience deploying AI at enterprise level.
  

Nice-to-Have

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• Fine‑tuning or training models.
  
• Familiarity with LangChain, Pydantic AI, or similar frameworks.
  
• Prompt engineering and evaluation techniques.
  
• Real‑time inference and streaming responses.
  
• Background in data engineering or ML engineering.
  
• Knowledge of RAG architectures.
  
• Contributions to open‑source AI/ML projects.
  

Tech Stack

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• Languages: Python, Bash.
  
• AI/ML: OpenAI API, Anthropic, HuggingFace, LangChain, Pydantic AI.
  
• Vector DBs: Pinecone, Chroma, Weaviate, FAISS.
  
• Backend: FastAPI, SQLAlchemy, Pydantic.
  
• Cloud: GCP (Vertex AI, Cloud Run), Terraform.
  
• CI/CD: GitHub Actions.
  
• Experiment Tracking: MLflow, Weights & Biases, or custom.
  
• Containers: Docker; Kubernetes optional.
  

What We Offer

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• Competitive compensation, including Stock Options.
  
• Access to state‑of‑the‑art tools and collaboration with leading experts.
  
• Flexible work arrangements with potential remote options.
  
• Opportunities for professional growth: conferences, conferences, publications.
  
• A culture focused on impact in AI and hardware.
  

Why Join Us

At Axiomatic_AI we drive innovation in AI for scientific and engineering applications. Your contributions will help bring new AI architectures that reason coherently and produce verifiable solutions to market, shaping the future of hardware and computing. xqbhyrx We celebrate diversity and encourage applicants who may not meet every qualification to apply; we are eager to consider a wide range of experiences and backgrounds.

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