AI/ML Engineer

AI/ML Engineer

Location: Remote

Duration: Fulltime Employment (FTE)

JOB SUMMARY

We are a next-generation AI-powered mission to level the playing field for small and medium-sized businesses (SMBs). By leveraging state-of-the-art large language models (LLMs), Agentic frameworks, and proprietary ML pipelines, we re redefining how marketing and advertising ecosystems operate, with intelligence, scale, and automation.

As a Agentic AI-Engineer, you ll be at the forefront of building our core intelligence stack. You will lead the design and implementation of cutting-edge machine learning systems, with a strong emphasis on LLMs/SLMs, agentic-based architectures, and real-time inference to power next-gen marketing and advertising workflows.

ESSENTIAL FUNCTIONS AND RESPONSIBILITIES

As an Agentic AI Engineer, you'll be at the forefront of developing autonomous AI systems. Your responsibilities will include:

• Building Agentic Systems: Design and deploy multi-agent pipelines using frameworks like LangGraph, AutoGen, or CrewAI to automate complex tasks.
• LLM/GenAI System Development: Architect and implement scalable LLM/GenAI systems specifically for marketing and advertising technology (MarTech/AdTech). This includes developing solutions for content generation, sentiment analysis, campaign optimization, audience segmentation, and personalization.
• Model Fine-Tuning: Develop and fine-tune language models (LLMs/SLMs) using both open-source and proprietary datasets for context-specific tasks like entity recognition, intent classification, and recommendation.
• Infrastructure and Deployment: Develop and manage scalable training and inference infrastructure, leveraging multi-GPU environments (A100/H100). Build robust data pipelines and model training loops to support rapid experimentation and deployment in real-time production environments.
• LLMOps and Best Practices: Implement best practices for model evaluation, A/B testing, and continuous learning. Contribute to LLMOps practices, including model monitoring, evaluation, and continuous deployment.
• Collaboration and Prototyping: Collaborate with product, data, and engineering teams to transform AI prototypes into scalable production services. Rapidly prototype research-backed features by translating research papers into working code.

KNOWLEDGE, SKILLS, ABILITIES, AND QUALIFICATIONS

• Experience: 5+ years of experience in ML/AI roles
• Agentic Frameworks: Hands-on experience with agent-based frameworks such as LangGraph, AutoGen, or CrewAI.
• Education: A Master's degree in engineering or computer science is required, with a PhD preferred.

Technical Skills:

• Strong expertise in Deep Learning & Natural Language Processing using frameworks like PyTorch or TensorFlow.
• Extensive experience fine-tuning foundation models (e.g., LLaMA, Mistral) and deploying inference pipelines.
• Proficiency with Hugging Face and popular fine-tuning techniques (LoRA, PEFT).
• Experience with Vector/Semantic search, RAG pipelines, or embedding optimization (PGVector, Pinecone, FAISS).

Infrastructure and Operations:

• Experience with LLMOps tooling (Weights & Biases, MLflow) and deploying ML systems in cloud environments (AWS, Google Cloud Platform, Azure).
• A deep understanding of GPU/memory optimization, distributed training, and batching strategies.
• Strong software engineering skills, including proficiency in Python, APIs, microservices, and containerization with Docker/Kubernetes.

Bonus Points:

• Knowledge of MarTech/AdTech data pipelines, targeting, or attribution models.
• Experience with real-time personalization systems or ad-serving infrastructure.
• Contributions to open-source LLM frameworks or research papers.
• Prior experience at a startup or growth-stage company.