Lead - Devloper Relations

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.