CUDA Engineer[Parallel Programming]

Digantara is building the world’s first maps for space, Space-Mission Assurance Platform™ (Space-MAP™). Space-MAP™ represents a revolutionary end-to-end infrastructure for sustainable space operations, offering a comprehensive space situational awareness (SSA) solution that simplifies and strengthens satellite operations in the face of the rapidly expanding commercialization of space.Space-MAP™ features advanced SSA analytics powered by cutting-edge astrodynamics algorithms that are optimized for fast turnaround time.
We are seeking a highly skilled and innovative CUDA Engineer to join our dynamic team. In this role, you will be instrumental in building efficient, scalable algorithms to process vast amounts of space situational awareness data and the optimization of existing code bases to achieve significant performance improvements. You will work closely with our astrodynamics and software teams to enhance the computation performance of algorithms.
Why Us?

• Competitive incentives, blazing team, frequent outings—pretty much everything that you have heard about a startup + you get to work on space technology.
• Hustle in a well-funded startup with a flat hierarchy that allows you to take charge of your responsibilities and create your own moonshot.

Responsibilities:

• Modify or rewrite functionally-ready algorithms and software solutions to optimize the computation of space situational awareness analytics.
• Collaborate closely with the Astrodynamics and software development teams to understand algorithmic requirements and project objectives.
• Identify and analyze performance bottlenecks in existing code bases and devise strategies for optimization.
• Optimize algorithms and code to achieve substantial performance improvements, aiming for orders of magnitude enhancements in computation time & resource utilization (RAM, CPUs, GPUs, etc.).
• Conduct comprehensive testing and profiling of code to ensure reliability, stability, and scalability of performance.
• Implement parallel processing, multi-threading, and GPU acceleration techniques to maximize computational efficiency. Use Spark, Dark, and Tenser-flow-like libraries to execute code faster.
• Convert code to User Define Function to be run in parallel in multipart machines or Containers.
• Document code optimization processes, best practices, and guidelines for knowledge sharing within the team.
• Participate actively in code reviews, offer feedback, and collaborate on code base enhancements.

Required Qualifications:

• Strong aptitude in parallel computing, distributed computing, GPU acceleration, and related frameworks.
• Proven experience in algorithm development and code optimization for computationally intensive applications.
• Strong programming skills in languages such as C++, Python, or CUDA.
• Experience with profiling and debugging tools to identify performance bottlenecks.
• Proficiency in dynamic programming techniques, which involve breaking down complex problems into smaller subproblems and reusing solutions to avoid redundant calculations.

Preferred Qualities

• Skills with Kubernetes, Spark, and Hadoop are preferable.
• Strong problem-solving skills and a passion for improving code performance.
• Excellent communication skills to work effectively in a multidisciplinary team.
• Ability to analyze complex algorithms and develop innovative optimization strategies.
• The capability to select and optimize data structures to enhance algorithm performance.
• Knowledge of MATLAB programming and cloud environments.

General Requirements

• Ability to think critically and make independent decisions.
• Interpersonal skills to enable working in a diverse and dynamic team.
• Maintain a regular and predictable work schedule.
• Verbal and written communication skills as well as organizational skills.

Job Location: Bengaluru, Karnataka, India
Work Type: Full Time

Contact Us: For additional queries or information, you may reach out to hiring@digantara.co.in