Axiomatic_AI
Join to apply for the
AI Platform Engineer
role at
Axiomatic_AI .
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 hardware design and simulation in the photonics and semiconductor industry. We seek highly motivated professionals to bring these innovations to life, driving the evolution from development to commercial product.
Position Overview As an AI Platform Engineer, you are the bridge between AI research and production software. Your role encompasses:
Build and maintain AI infrastructure: model serving, vector databases, embedding pipelines
Enable AI developers to deploy their work 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, reliability
Collaborate with backend engineers to integrate AI capabilities into the product
Key Responsibilities
AI Infrastructure
Deploy and serve LLMs (OpenAI, Anthropic, HuggingFace, fine‑tuned models)
Optimize inference latency and costs
Implement caching, rate limiting, and retry strategies
MLOps & Pipelines
Version models, prompts, datasets, and evaluation results
Implement experiment tracking (Weights & Biases)
Build CI/CD pipelines for model deployment
Monitor model performance and drift
Set up logging and observability for AI services
API Development
Design and implement APIs (FastAPI)
Create endpoints for prompt testing, model selection, and evaluation
Integrate AI services with backend application
Ensure API reliability, security, and performance
Collaboration & Enablement
Work with AI Developers to productionize experiments improving user workflows
Define workflows: notebook/test repo → PR → staging → production
Document AI infrastructure and best practices
Review code and mentor AI developers on software practices
Required Skills & Experience Must-Have
7+ years of software engineering experience (Python preferred)
Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar
Understanding 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
Operating experience with AI deployment in enterprise environments
Nice-to-Have
Experience fine‑tuning or training models
Familiarity with LangChain, Pydantic AI or similar frameworks
Knowledge of prompt engineering and evaluation techniques
Experience with real‑time inference and streaming responses
Background in data engineering or ML engineering
Understanding of RAG architectures
Contributions to open‑source AI/ML projects
Current Stack
Languages:
Python (primary), Bash
AI/ML:
OpenAI API, Anthropic, HuggingFace, LangChain, Pydantic AI
Vector DBs:
Pinecone, Chroma, Weaviate, or 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
Stock Options Plan:
Empowering you to share in our success and growth.
Cutting‑Edge Tools:
Access to state‑of‑the‑art tools and collaborative opportunities with leading experts in AI, physics, hardware and electronic design automation.
Work‑Life Balance:
Flexible work arrangements in one of our offices with potential options for remote work.
Professional Growth:
Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
Impact‑Driven Culture:
Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.
Why Join Us At Axiomatic_AI, you will work on technology that drives innovation in AI for scientific and engineering applications aligned with our 10X30 mission. This is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions, eventually shaping the future of hardware and computing. We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI with a focus on formal consistency. If you’re ready to take your expertise in AI and physics to the next level, we want to hear from you!
Worried about not meeting every qualification? Studies show that women and people of color are less likely to apply for jobs unless they meet every listed requirement. At Axiomatic_AI, we are dedicated to creating a diverse, inclusive, and authentic workplace. If this role excites you but your background doesn’t perfectly match every qualification, we still encourage you to apply. You could be the perfect fit for this position or another opportunity with us.
#J-18808-Ljbffr
AI Platform Engineer
role at
Axiomatic_AI .
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 hardware design and simulation in the photonics and semiconductor industry. We seek highly motivated professionals to bring these innovations to life, driving the evolution from development to commercial product.
Position Overview As an AI Platform Engineer, you are the bridge between AI research and production software. Your role encompasses:
Build and maintain AI infrastructure: model serving, vector databases, embedding pipelines
Enable AI developers to deploy their work 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, reliability
Collaborate with backend engineers to integrate AI capabilities into the product
Key Responsibilities
AI Infrastructure
Deploy and serve LLMs (OpenAI, Anthropic, HuggingFace, fine‑tuned models)
Optimize inference latency and costs
Implement caching, rate limiting, and retry strategies
MLOps & Pipelines
Version models, prompts, datasets, and evaluation results
Implement experiment tracking (Weights & Biases)
Build CI/CD pipelines for model deployment
Monitor model performance and drift
Set up logging and observability for AI services
API Development
Design and implement APIs (FastAPI)
Create endpoints for prompt testing, model selection, and evaluation
Integrate AI services with backend application
Ensure API reliability, security, and performance
Collaboration & Enablement
Work with AI Developers to productionize experiments improving user workflows
Define workflows: notebook/test repo → PR → staging → production
Document AI infrastructure and best practices
Review code and mentor AI developers on software practices
Required Skills & Experience Must-Have
7+ years of software engineering experience (Python preferred)
Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar
Understanding 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
Operating experience with AI deployment in enterprise environments
Nice-to-Have
Experience fine‑tuning or training models
Familiarity with LangChain, Pydantic AI or similar frameworks
Knowledge of prompt engineering and evaluation techniques
Experience with real‑time inference and streaming responses
Background in data engineering or ML engineering
Understanding of RAG architectures
Contributions to open‑source AI/ML projects
Current Stack
Languages:
Python (primary), Bash
AI/ML:
OpenAI API, Anthropic, HuggingFace, LangChain, Pydantic AI
Vector DBs:
Pinecone, Chroma, Weaviate, or 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
Stock Options Plan:
Empowering you to share in our success and growth.
Cutting‑Edge Tools:
Access to state‑of‑the‑art tools and collaborative opportunities with leading experts in AI, physics, hardware and electronic design automation.
Work‑Life Balance:
Flexible work arrangements in one of our offices with potential options for remote work.
Professional Growth:
Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
Impact‑Driven Culture:
Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.
Why Join Us At Axiomatic_AI, you will work on technology that drives innovation in AI for scientific and engineering applications aligned with our 10X30 mission. This is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions, eventually shaping the future of hardware and computing. We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI with a focus on formal consistency. If you’re ready to take your expertise in AI and physics to the next level, we want to hear from you!
Worried about not meeting every qualification? Studies show that women and people of color are less likely to apply for jobs unless they meet every listed requirement. At Axiomatic_AI, we are dedicated to creating a diverse, inclusive, and authentic workplace. If this role excites you but your background doesn’t perfectly match every qualification, we still encourage you to apply. You could be the perfect fit for this position or another opportunity with us.
#J-18808-Ljbffr