Lead AI Engineer at Merkle | AdTechTalent
Home / Jobs / Lead AI Engineer Engineering 4 months ago Hybrid
Merkle
Lead AI Engineer
leadership generative AI transformers deep learning LLM multimodal agentic frameworks RAG Python FastAPI Flask Docker AWS Azure GCP Apache Spark Hadoop MongoDB PyTorch TensorFlow knowledge graphs machine learning model deployment MLOps CI/CD API development data engineering prompt engineering fine-tuning RLHF LoRA QLoRA predictive modeling vector search SQL
Ready to apply?
Join Merkle and work on a role built for experienced AdTech operators.
Quick snapshot
Bengaluru, India
Full-time
Full job description Lead Generative AI Engineer role requiring strong expertise in deep learning, transformer architectures, and building advanced GenAI applications beyond basic RAG systems. Responsibilities include designing and developing multimodal and agentic AI applications, knowledge graph-assisted AI systems, scalable API and microservice deployment, cloud ML/AI system deployment and monitoring (AWS, Azure, GCP), big data technology utilization (Apache Spark, Hadoop, MongoDB), transformer model optimization, fine-tuning and evaluation, information retrieval system development, predictive modeling, and cross-functional collaboration. Must have 5+ years software development experience including ML production deployment, 2+ years deep learning/GenAI experience, advanced Python skills, backend framework experience (Flask, FastAPI, Django), and strong math foundations. Mentorship and documentation duties included.
What you'll do Build conversational and non-conversational, multimodal, and agentic AI applications using LLMs and frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, or similar Similar jobs
More roles worth a look Related opportunities based on specialty and working model so candidates can keep momentum.
TripleLift
Detroit, United States; New York, US • 5 months ago
$75K – $95K
accounting payroll compensation
TripleLift
Pune, India • 5 months ago
ad ops programmatic campaign management
TripleLift
Design AI workflows incorporating reasoning, planning, tool-use, memory, grounding, and external system integrations
Develop Knowledge Graph-assisted AI systems including entity extraction, linking, and KG-augmented retrieval
Ensure safety, consistency, and hallucination-control through structured evaluation and guardrails
Transform models into scalable APIs and microservices using Python, FastAPI/Flask, Docker
Deploy and monitor ML/AI systems in AWS/Azure/GCP, optimizing for cost, latency, and reliability
Collaborate with MLOps teams on CI/CD pipelines, model versioning, monitoring, and automated evaluation
Work with big data technologies including Apache Spark, Hadoop, and NoSQL databases such as MongoDB
Build and optimize transformer-based and multimodal models using deep learning frameworks (e.g., PyTorch, TensorFlow)
Implement fine-tuning, alignment (RLHF/RLAIF), LoRA/QLoRA, pruning, and model evaluation pipelines
Develop information retrieval systems including hybrid dense–sparse retrieval, ranking, knowledge graphs, and relevance optimization
Build predictive models and ML pipelines from scratch including data preparation, feature engineering, and model selection
Work cross-functionally with CX, engineering, and product stakeholders to translate business needs into AI solutions
Document models, experiments, evaluation frameworks, and deployment processes
Mentor junior engineers and contribute to internal best practices, reusable components, and R&D initiatives Requirements Minimum 5+ years of hands-on software development experience including building and deploying machine learning models into production 2+ years of experience working with deep learning, GenAI, or transformer-based architectures Demonstrated experience building GenAI applications beyond simple RAG (e.g., agents, multimodal, custom LLM fine-tuning) Experience integrating AI systems in enterprise-grade environments Advanced Python programming skills Experience with API development and data engineering Experience with backend frameworks: Flask, FastAPI, Django Knowledge of predictive modelling, deep learning, optimization, embeddings, vector search, model evaluation Experience with generative AI technologies: LLMs, RAG, multimodal architectures, agents, prompt engineering, grounding, knowledge graphs Hands-on experience deploying and scaling AI systems on AWS, Azure, or GCP Strong understanding of data pipelines and large-scale processing using Apache Spark, Hadoop, MongoDB Math foundations in linear algebra, probability, statistics Tech stack Python SQL Flask FastAPI Django PyTorch TensorFlow LangChain LangGraph LlamaIndex AutoGen Docker AWS Azure GCP Apache Spark Hadoop MongoDB
Apply now Ready to take the next step in your career? Click the button below to continue to the application process.
Company
Merkle Merkle, a dentsu company, powers the experience economy. For more than 35 years, the company has put people at the heart of its approach to digital business transformation. As the only integrated experience consultancy in the world with a heritage in data science and business performance, Merkle delivers holistic, end-to-end experiences that drive growth, engagement, and loyalty. Merkle’s expertise has earned recognition as a “Leader” by top industry analyst firms, in categories such as digital transformation and commerce, experience design, engineering and technology integration, digital marketing, data science, CRM and loyalty, and customer data management. With more than 16,000 employees, Merkle operates in 30+ countries throughout the Americas, EMEA, and APAC.
Industry
Business Consulting and Services
Website
https://www.merkle.com
Posted
4 months ago
Category: Engineering
Chicago, United States; Detroit, United States; New York, US; Toronto, Canada • 5 months ago
salesforce apex lightning web components
