3 days ago
Pune, IndiaMid Level
Responsibilities
- Build conversational, non-conversational, multimodal, and agentic AI applications using LLMs and agentic frameworks.
- Design AI workflows incorporating reasoning, planning, tool use, memory, grounding, and external system integrations.
- Develop knowledge-graph-assisted AI systems, including entity extraction, entity linking, and knowledge-graph-augmented retrieval.
- Implement safety controls, structured evaluation, guardrails, and hallucination-control mechanisms.
- Transform models into scalable APIs and microservices and deploy, monitor, and optimize AI systems for cost, latency, and reliability.
- Build and optimize transformer-based and multimodal models, including fine-tuning, alignment, LoRA/QLoRA, pruning, and evaluation pipelines.
- Develop information-retrieval systems, ranking systems, knowledge graphs, predictive models, and ML pipelines.
- Collaborate with CX, engineering, product, data science, and MLOps teams to translate business needs into AI solutions.
- Document models, experiments, evaluation frameworks, and deployment processes; mentor junior engineers and contribute to reusable components and R&D initiatives.
Requirements
- Advanced Python and SQL skills with robust API development and data engineering experience.
- Experience with Flask, FastAPI, or Django and production deployment of machine learning models.
- Strong knowledge of deep learning, predictive modeling, optimization, embeddings, vector search, model evaluation, LLMs, RAG, multimodal architectures, agents, prompt engineering, grounding, and knowledge graphs.
- Hands-on experience deploying and scaling AI systems on AWS, Azure, or GCP.
- Experience with Apache Spark, Hadoop, MongoDB, data pipelines, and large-scale processing.
- Understanding of linear algebra, probability, and statistics.
- Minimum 3–4 years of hands-on software development experience, including building and deploying machine learning models into production.
- At least 2 years of experience with deep learning, GenAI, or transformer-based architectures.
- Demonstrated experience building GenAI applications beyond simple RAG, such as agents, multimodal systems, or custom LLM fine-tuning.
- Experience integrating AI systems in enterprise-grade environments.
- Clear communication, strong problem-solving ability, collaboration, experimentation, and willingness to work in a hybrid structure.
Benefits
- Permanent, full-time employment.
- Hybrid work structure requiring at least two days per week in the Pune office for team connection and knowledge exchange.
- Opportunity to work on intelligent agents, multimodal experiences, personalization systems, and knowledge-grounded AI solutions for global brands.
- Opportunities to mentor engineers and contribute to internal best practices and R&D initiatives.
Tech Stack
Apache HadoopApache SparkAWSAzureDockerFastAPIFlaskGoogle Cloud PlatformMongoDBPythonPyTorchSQLTensorFlow
Categories
About Dentsu
Dentsu is a global advertising and marketing services group that plans and buys media, develops creative campaigns, and builds data- and technology-led customer experiences for brands. It earns revenue from agency fees and media services across a network that includes Carat, iProspect, and Merkle. Founded in 1901 and headquartered in Tokyo, Dentsu is publicly traded in Japan and serves clients across many sectors worldwide.