Digantara is a leading Space Surveillance and Intelligence company focused on ensuring orbital safety and sustainability. With expertise in space-based detection, tracking, identification, and monitoring, Digantara provides comprehensive domain awareness across all regimes, enabling end-users to gain actionable intelligence on a single platform. At the core of its infrastructure lies a sophisticated integration of hardware and software capabilities aligned with the key principles of situational awareness: perception (data collection), comprehension (data processing), and prediction(analytics). This holistic approach empowers Digantara to monitor all Resident Space Objects (RSOs) in orbit, fostering comprehensive domain awareness.
The Algorithm Optimization Engineer will improve the computational efficiency and scalability of space domain awareness algorithms by redesigning algorithms, optimizing data structures, and enhancing performance across large-scale data pipelines.
Ideal Candidate
Demonstrated ability to independently own and drive end-to-end optimization of algorithms, from performance analysis and bottleneck identification to redesign, implementation, and validation of optimized solutions.
Strong expertise in algorithms, data structures, and performance tuning for complex computational workflows.
Proven ability to achieve significant performance improvements through algorithmic design rather than brute-force scaling of compute resources.
Analyse existing Space Domain Awareness (SDA) pipelines to identify computational, numerical, and data-access bottlenecks.
Design and implement optimized algorithms using efficient data structures, indexing strategies, and pruning techniques.
Improve computational performance through thoughtful restructuring of algorithms and workflows.
Implement parallelized or GPU-accelerated components where beneficial while maintaining numerical precision and efficiency.
Collaborate with domain experts to validate optimized algorithms and ensure correctness of approximations.
Establish profiling, benchmarking, and performance evaluation frameworks for optimization efforts.
Develop regression testing and validation mechanisms to maintain correctness during optimization cycles.
Apply robust software engineering practices including code reviews, documentation, and maintainable implementations.
Document optimization strategies, trade-offs, and validation outcomes to support long-term maintainability.
Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative field.
4+ years of experience in algorithm optimization, performance engineering, or large-scale computational systems.
Strong understanding of algorithms and data structures for large-scale search, filtering, or assignment problems.
Proficiency in Python and at least one performance-oriented language such as C, C++, or CUDA.
Experience profiling and optimizing computational systems with attention to memory usage and data access patterns.
Familiarity with parallel programming models and concurrency concepts across CPU or GPU environments.
Solid grounding in numerical methods, linear algebra, and precision management.
Experience optimizing spatial, temporal, or graph-based computational problems.
Familiarity with hybrid CPU/GPU computational pipelines.
Experience working in high-performance computing or cloud-based computational environments.
Strong analytical thinking and problem-solving capability.
Ability to work collaboratively with interdisciplinary technical teams.
Strong documentation and communication skills to support long-term system maintainability.
High ownership mindset with the ability to operate in complex technical environments.
Job Location: Hebbal, Bengaluru
.jpeg)
