4 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead experimentation, design, and development of agentic AI systems that monitor model performance, trigger experiments, tune hyperparameters, improve ranking policies, and orchestrate ML workflows.
- Apply LLMs, embeddings, retrieval-augmented architectures, and multimodal generative models to semantic understanding, content classification, and user preference modeling.
- Design intelligent agents and LLM-powered applications that automate decision-making tasks such as candidate generation tuning, feature selection, and context-aware content curation.
- Build and operate machine learning models for forecasting, classification, and prediction using diverse, high-volume data sources.
- Develop experimentation workflows and end-to-end pipelines for data preparation, model training, evaluation, deployment, monitoring, and retraining.
- Use statistical techniques to monitor model performance, identify drift and failure modes, and improve model explainability, accuracy, and compliance.
- Support proof-of-concept and pilot projects involving emerging ML and AI technologies.
- Contribute to ML and AI thought leadership through blogs, case studies, technical talks, and industry conferences.
- Collaborate with engineering, product, business, creative, data, and infrastructure stakeholders to align ML initiatives with strategic priorities.
- Document designs, development processes, and best practices and participate in design reviews, sprint planning, and technical discussions.
Requirements
- Bachelor’s or master’s degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Operations Research, Economics, Analytics, or a related field; a PhD is a plus.
- At least 8 years of industry experience in machine learning or data science.
- Deep proficiency in Python and experience with one or more of PyTorch, TensorFlow, or Scikit-learn.
- Strong understanding of regression, tree-based models, clustering, time series, NLP, deep learning, and real-world data applications.
- Hands-on experience building LLM-powered applications, chatbots, retrieval systems, generative models, agentic systems, or multi-agent systems.
- Experience with AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, n8n, or ReAct-style agents.
- Experience creating and maintaining prompt templates, chains, workflows, and MCP tools, servers, or capabilities.
- Experience integrating vector databases such as MilvusDB, FAISS, Pinecone, or Chroma for semantic search and memory.
- Experience deploying ML workflows and models in production, including continuous monitoring, evaluation, and retraining.
- Strong experience with big-data ecosystems such as Spark and Hadoop and cloud platforms such as Azure, AWS, and GCP/Vertex AI.
- Understanding of data pipelines, APIs, cloud platforms, and end-to-end ML solution development.
- Strong problem-solving, analytical, communication, collaboration, and adaptability skills.
Benefits
- Modern work environment and flexible schedule.
- Internal opportunities to move roles and try bridge assignments with different teams.
- Free meals all days of the week, gym or yoga classes, drink cart Thursdays, and workplace social activities.
- Opportunities for continuous learning and career progression through the InMobi Live Your Potential program.
- Reasonable accommodations are provided to qualified individuals with disabilities throughout the hiring process and workplace.
Tech Stack
Categories
About InMobi
InMobi builds a mobile advertising and consumer engagement platform for advertisers and publishers and operates Glance, a lock‑screen content and commerce service. It sells programmatic ad buying, monetization tools, and AI-driven personalization across apps, TVs, and the open web. Founded in 2007 and headquartered in Singapore, its ad network reaches over 2 billion people in 150+ countries and serves more than 30,000 brands.