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We are looking for a skilled professional to join our team as a senior member of technical staff. In this role, you will be responsible for designing and implementing backend infrastructure and APIs, writing high-quality code that is robust, readable, and scalable, and troubleshooting and debugging applications.
This is an exciting opportunity for individuals who possess strong problem-solving skills and expertise in building complex, high-performance systems. We are looking for someone with proven experience in building end-to-end AI/ML applications using TensorFlow, PyTorch, and Keras, with strong MLOps practices for model deployment and monitoring.
The ideal candidate will have a solid foundation in machine learning, deep learning, and AI integration into production systems with real-world performance trade-off understanding. Exposure to NLP, Computer Vision, or Reinforcement Learning and understanding of model interpretability and responsible AI practices is also desired.
In addition to technical skills, we are looking for individuals who are skilled in system strategies, including load balancing, caching, service discovery, rate limiting, disaster recovery, and observability. Hands-on experience with Java Spring Boot, Python, Android, and containerized deployments using Docker and Kubernetes is also required.
About the Role- Design and implement backend infrastructure and APIs
- Write high-quality code that is robust, readable, and scales
- Troubleshoot & debug applications
- Avoid quick fixes and instead adopt problem-solving as a way of life - always go to the root cause
- Collaborate with the team to discuss and implement ideas
- Build responsive, robust, and optimized applications
Requirements
- 6–10 years of experience in software development with strong problem-solving skills and expertise in building complex, high-performance systems.
- Proven expertise in building end-to-end AI/ML applications using TensorFlow, PyTorch, and Keras, with strong MLOps practices for model deployment and monitoring.
- Solid foundation in machine learning, deep learning, and AI integration into production systems with real-world performance trade-off understanding.
- Exposure to NLP, Computer Vision, or Reinforcement Learning and understanding of model interpretability and responsible AI practices.
- Deep experience in designing scalable, distributed systems using microservices, event-driven architecture, and principles like the CAP theorem and fault tolerance.
- Skilled in system strategies, including load balancing, caching, service discovery, rate limiting, disaster recovery, and observability.
- Hands-on with Java Spring Boot, Python, Android, and containerized deployments using Docker and Kubernetes.
- Strong knowledge of RESTful services, Kafka-based messaging, multithreading, and inter-process communication.
- Proficient in RDBMS (SQL), familiar with PostgreSQL, Redis, MongoDB, and well-versed in object-oriented design and design patterns.
- Experienced in version control (Git), performance tuning, algorithm design, and large-scale system optimization.
