AI/ML Engineer

We are seeking an AI/ML Engineer – Agents to help build the core intelligence layer of our AI-powered MarTech and AdTech platform. This role will focus on designing, developing, and deploying agentic AI systems , LLM-powered applications , and real-time inference pipelines that drive intelligent automation, personalization, and decision-making at scale.

This is a high-impact, hands-on engineering role for someone who thrives in fast-moving environments and wants to help shape next-generation AI products from the ground up.

Key Responsibilities

• Design and deploy agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI , or similar.


• Build and scale LLM/GenAI applications for MarTech and AdTech use cases, including content generation, campaign optimization, audience segmentation, personalization, and workflow automation.


• Fine-tune and optimize LLMs/SLMs for domain-specific tasks such as classification, extraction, recommendation, and intent understanding.


• Develop and manage training and inference pipelines for production-scale ML systems.


• Build scalable infrastructure for real-time and batch inference , experimentation, and deployment.


• Implement best practices for evaluation, A/B testing, model monitoring, and continuous improvement .


• Partner closely with product, data, and engineering teams to turn prototypes and research into production-ready AI services .


• Rapidly prototype and apply emerging research to practical product use cases.

Qualifications

• 3+ years of experience in AI/ML engineering , machine learning, or applied NLP roles.


• Master’s degree in Computer Science, Engineering, or a related field required; PhD preferred .


• Hands-on experience with agent-based AI frameworks such as LangGraph, AutoGen, CrewAI , or similar.


• Strong expertise in deep learning and natural language processing using frameworks such as PyTorch or TensorFlow .


• Experience fine-tuning and deploying foundation models such as LLaMA , Mistral , or similar.


• Strong experience with Hugging Face , LoRA , PEFT , and modern fine-tuning workflows.


• Experience with RAG pipelines , vector databases , semantic search , and embedding optimization tools such as FAISS , Pinecone , or PGVector .


• Experience deploying ML systems in cloud environments such as AWS , GCP , or Azure .


• Strong software engineering skills in Python , APIs, microservices, and containerized environments such as Docker and Kubernetes .


• Solid understanding of GPU optimization , distributed training , and inference performance tuning.

Preferred Qualifications

• Experience in MarTech , AdTech , personalization, targeting, or attribution systems.


• Experience with real-time decisioning or ad-serving systems.


• Contributions to open-source AI/LLM frameworks or published research.


• Prior experience in a startup or high-growth environment .