2 hours 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
We are dentsu. We team together to help brands predict and plan for disruptive future opportunities and create new paths to growth in the sustainable economy. We know people better than anyone else and we use those insights to connect brand, content, commerce and experience, underpinned by modern creativity. We are the network designed for what’s next.