TAAS Partners
Website:
taaspartners.com
Job details:
About Client - They are a Series A funded setup with about USD 2Mn Revenue and Growing, working in Memory Utliziation for AI Agents
Role Overview
As a Developer Relations (DevRel) Engineer - AI/ML, you will be the technical bridge between our advanced AI engineering teams and the broader developer ecosystem. You will combine your software engineering expertise with a passion for community building to drive the adoption of our cutting-edge AI products. You are a builder, an educator, and an advocate who empowers developers to build incredible applications using our technology.
Key Responsibilities
1. Technical Advocacy & Content Creation
- Create high-quality developer resources, including SDKs, cookbooks, technical tutorials, reference architectures, and video demos.
- Build real-world implementation patterns across generative AI, multi-agent workflows, and retrieval-augmented generation (RAG).
- Write production-ready example code and notebooks showing how to train, fine-tune, and deploy models efficiently.
2. Community Engagement & Enablement
- Represent the company at AI/ML conferences, hackathons, meetups, and webinars.
- Cultivate and manage our technical communities across platforms like Discord, Reddit, and GitHub Discussions.
- Host office hours, AMAs, and workshops to reduce the "time-to-first-value" for new developers integrating with our AI APIs.
3. Inbound Product Advocacy
- Act as the voice of the community by gathering actionable feedback and synthesizing it into feature requests and friction logs.
- Collaborate closely with Product and Engineering teams to influence product roadmaps based on ecosystem trends and user pain points.
4. Ecosystem Integration
- Engage with open-source AI communities and integrate our software stacks into broader industry ecosystems (e.g., PyTorch, Hugging Face, LangChain, vLLM).
- Help developers debug API issues and optimize their ML and inference workflows.
Required Qualifications
- Experience: 4-8 years of experience in developer relations, developer advocacy, or as a machine learning engineer transitioning into a community-facing role.
- Technical Skills: Proficiency in Python. Hands-on experience with modern AI/ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face, LangChain).
- AI/ML Workflows: Deep understanding of model training, fine-tuning, inference, vector databases, and RAG pipelines.
- Communication: Exceptional ability to distill complex technical concepts into clear, structured, and engaging language for both technical and non-technical audiences.
- Portfolio: A proven track record of technical work (e.g., GitHub repositories, published tutorials, technical talks, or open-source contributions).
Preferred Qualifications
- Experience deploying or optimizing ML models in production environments.
- Hands-on experience with cloud infrastructure, GPU compute, or MLOps platforms.
- An existing, active presence in AI/ML developer communities.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes.
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