4 months ago
Pune, IndiaStaff+
Responsibilities
- Build conversational, non-conversational, multimodal, and agentic AI applications using LLMs and agent frameworks.
- Design AI workflows involving reasoning, planning, tool use, memory, grounding, and external system integrations.
- Develop knowledge-graph-assisted systems with entity extraction, entity linking, and knowledge-graph-augmented retrieval.
- Create evaluation frameworks, guardrails, and controls for safety, consistency, and hallucination reduction.
- Build scalable APIs and microservices and deploy, monitor, and optimize AI/ML systems in cloud environments.
- Develop and optimize transformer-based and multimodal models using deep learning frameworks.
- Implement fine-tuning, RLHF/RLAIF alignment, LoRA/QLoRA, pruning, model evaluation, and information retrieval pipelines.
- Build predictive models and machine learning pipelines involving data preparation, feature engineering, and model selection.
- Collaborate with MLOps teams on CI/CD, model versioning, monitoring, and automated evaluation.
- Partner 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 reusable components, internal best practices, and R&D initiatives.
Requirements
- Minimum 5–6 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, Generative AI, or transformer-based architectures.
- Demonstrated experience building GenAI applications beyond simple RAG, such as agents, multimodal applications, or custom LLM fine-tuning.
- Advanced Python and SQL skills with robust API development and data engineering experience.
- Experience with Flask, FastAPI, or Django.
- Knowledge of predictive modeling, deep learning, optimization, embeddings, vector search, and model evaluation.
- Experience with LLMs, RAG, multimodal architectures, agents, prompt engineering, grounding, and knowledge graphs.
- Hands-on experience deploying and scaling AI systems using AWS, Azure, or GCP.
- Experience with Apache Spark, Hadoop, MongoDB, data pipelines, and large-scale processing.
- Understanding of linear algebra, probability, statistics, and deep learning architectures including RNNs, LSTMs, and Transformers.
- Experience integrating AI systems in enterprise-grade environments.
- Strong problem-solving, communication, collaboration, experimentation, and stakeholder-management abilities.
Benefits
- Permanent, full-time position.
- Hybrid work structure requiring at least two days per week in the office for team connection and knowledge exchange.
- Located at DGS India, Pune, Baner M.
Tech Stack
Apache HadoopApache SparkAWSAzureDjangoDockerFastAPIFlaskGoogle 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.