AI/ML Engineer at Encora10

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.