Principal AI/ML Engineer

Principal LLM & ML Engineer

JOB SUMMARY

Our client is a next-generation AI-powered MarTech and AdTech startup on a mission to level the playing field for small and medium-sized businesses. By leveraging state-of-the-art large language models, agentic frameworks, and proprietary ML pipelines, they’re redefining how marketing and advertising ecosystems operate, with intelligence, scale, and automation.

 As a Principal LLM & ML 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

• Architect and implement scalable LLM/GenAI systems optimized for MarTech/AdTech use cases (e.g., content generation, sentiment analysis, resonance analysis, recommended marketing strategies, campaign optimization, audience segmentation, personalization, targeting..etc.)
• Develop and fine-tune language models (LLMs/SLMs) for context-specific using open-source and proprietary datasets for use cases such as entity recognition, intent classification, recommendation, and ranking.
• Designing and deploying agentic systems (multi-agent pipelines using frameworks such as LangGraph, AutoGen, or CrewAI)
• Maintain best practices for model evaluation, A/B testing, and continuous learning in real-time production environments.
• Develop scalable training and inference infrastructure leveraging multi-GPU environments (A100/H100 preferred)
• Build robust data pipelines and model training loops that support rapid experimentation and deployment.
• Contribute to LLMOps practices, including model monitoring, evaluation, and continuous deployment
• Collaborate with product, data, and engineering teams to turn AI prototypes into scalable production services.
• Rapidly prototype research-backed features by translating research papers into working code

KNOWLEDGE, SKILLS, ABILITIES, AND QUALIFICATIONS

• 6+ years of experience in ML/AI roles, with at least 2+ years building with LLMs/SLMs
• Master’s degree in engineering or computer science, PhD preferred.
• Strong experience in Deep Learning & Natural Language Processing (PyTorch, or TensorFlow)
• Hands-on experience with fine-tuning foundation models (LLaMA, Mistral, GPT-like models) and deploying inference pipelines.
• Proficiency with Hugging Face and popular LLM training & fine-tuning techniques (LoRA, PEFT, etc.)
• Experience with Vector/Semantic search, RAG pipelines, or embedding optimization (PGVector, Pinecone, FAISS, Redis Vector)
• Familiarity with agent-based frameworks (MCP, A2A, LangGraph, ReAct, AutoGen, CrewAI, LangChain Agents, etc.).
• Experience with LLMOps tooling and frameworks (Weights & Biases, MLflow, Prompt Layer, etc.)
• Experience deploying ML systems in cloud environments (AWS, GCP, Azure) and using MLOps tools.
• Understanding of GPU/memory optimization, distributed training, and batching strategies
• Strong software engineering skills (Python, APIs, microservices, containerization with Docker/K8s)
• Strong communication skills and ability to thrive in fast-paced, cross-functional teams.
• A major plus is 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 startup or growth-stage company experience.