This role is for one of the Weekday's clients
Min Experience: 3 years
Location: Bangalore
JobType: full-time
We are a fast-growing, VC-backed startup on a mission to supercharge the machine learning development lifecycle. Our platform empowers ML teams to rapidly build, iterate, and deploy high-performing models by providing powerful tools that enhance experimentation, reproducibility, and collaboration. Our engineering culture is fast-paced, deeply technical, and focused on solving meaningful problems that have real-world impact.
Role Overview:
We are looking for a passionate and skilled SDE 2 – Backend Developer to join our growing engineering team. In this role, you’ll design, build, and maintain large-scale backend systems that power our platform. You’ll be working on real-time stream processing pipelines, scalable APIs, and robust infrastructure that supports high-throughput ML workflows.
As part of our core backend team, you’ll work closely with product managers, ML engineers, and DevOps to build backend services that are performant, reliable, and maintainable.
Requirements
Key Responsibilities:
- Design and implement scalable, low-latency backend systems using Java or Python.
- Build and optimize real-time data processing pipelines that handle large volumes of structured and unstructured data.
- Develop RESTful and/or gRPC APIs for internal and external use.
- Collaborate with cross-functional teams to understand requirements and deliver features that align with business and technical objectives.
- Write clean, testable, and maintainable code with strong focus on performance and scalability.
- Own features end-to-end: from design, development, testing, deployment, to monitoring.
- Actively participate in code reviews, design discussions, and architecture planning.
What We’re Looking For:
- 3+ years of hands-on backend development experience with Java or Python.
- Solid understanding of system design, data structures, and algorithms.
- Strong experience with real-time streaming systems such as Apache Kafka, Flink, or Apache Spark Streaming.
- Experience building scalable microservices and working with cloud-native infrastructure (AWS/GCP/Azure).
- Familiarity with containerization and orchestration tools (Docker, Kubernetes).
- Experience with CI/CD pipelines and DevOps best practices.
- A product mindset – ability to think through use cases and customer needs.
- A strong sense of ownership, craftsmanship, and a desire to ship quality code.
Nice to Have:
- Experience in building developer platforms or internal tooling for ML/AI workflows.
- Familiarity with distributed systems and event-driven architectures.
- Exposure to ML lifecycle tools (like MLflow, Kubeflow, or similar).