about 4 hours ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Own the full machine learning lifecycle: problem scoping, data exploration, pipeline development, model training, deployment, and monitoring in production.
- Design and build Agentic AI systems that combine time-series modeling, signal processing, and generative AI.
- Develop and deploy machine learning models for forecasting, anomaly detection, and pattern recognition in industrial sensor data.
- Integrate classical statistical methods, deep learning, and GenAI techniques to generate actionable insights from complex datasets.
- Build scalable data pipelines and ML systems that operate reliably in production environments.
- Collaborate with Product, Engineering, and Algorithm teams to define solutions and translate customer needs into technical implementations.
- Partner with customers and internal stakeholders to identify new data-driven opportunities and emerging use cases.
- Implement robust evaluation, monitoring, and drift detection systems for live ML/Agentic applications.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related technical field.
- 4+ years of experience in Machine Learning, Applied AI, or related fields.
- Proven ability to own and deliver end-to-end ML systems in production environments.
- Strong experience in time-series modeling, forecasting, anomaly detection, and feature engineering.
- Hands-on experience with Python and ML frameworks such as Pydantic, PTorch, TensorFlow, or Scikit-learn.
- Familiarity with generative AI systems, including LLMs and agent-based architectures.
- Strong understanding of data pipelines and production ML systems.
- Experience working in Agile, fast-paced, cross-functional environments.
- Strong collaboration skills with distributed teams across engineering, product, and data functions.
Benefits
- Stock options
- Paid parental leave
- Flex PTO