Analyst - Algorithm Research & Development - Chennai, Tamil Nadu

Only for registered members Chennai, Tamil Nadu, India

19 hours ago

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Description · Company : · Enormous Enterprise LLC. · Location : · Chennai, Tamil Nadu, India. · Pay : · DOE. · Role : · Analyst, Algorithm Research & Development (CUDA). · Job Summary · Our Client is a global leader in diversified electronics for the semiconductor manufacturing e ...
Job description

Description
Company :
Enormous Enterprise LLC.

Location :
Chennai, Tamil Nadu, India.

Pay :
DOE.

Role :
Analyst, Algorithm Research & Development (CUDA).

Job Summary
Our Client is a global leader in diversified electronics for the semiconductor manufacturing ecosystem.

Virtually every electronic device in the world is produced using our technologies.

No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us.

Our client invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays.

The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development.

Our Client focuses more than average on innovation and in 2019 we invested 15% of sales back into R&D.

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the worlds leading technology providers to accelerate the delivery of tomorrows electronic devices.

Life here is exciting and our teams thrive on tackling really hard problems.

There is never a dull moment with us.

Key Responsibilities

  • Develop algo focusing on CUDA acceleration, CPU to GPU conversion of image processing algos and models.
  • Stay updated with emerging technologies and industry best practices.
  • Bring new ideas to the team by exploring modern frameworks or tools that could enhance the platforms capabilities.

Required Qualifications

  • Masters degree in Computer Science or a related field, or Bachelors degree in Computer Science (or related) with at least 3 years of hands-on web application development experience.

Experience

  • Minimum 3+ years of professional algo development experience focusing on CUDA acceleration, CPU to GPU conversion of image processing algos and models.
  • Proven track record of delivering software projects from design to deployment.

Programming Skills

  • Deep understanding of operating systems, computer networks, and high performance applications.
  • Good mental model of the architecture of a modern distributed systems that is comprised of CPUs, GPUs, and accelerators.
  • Experience with deployments of deep-learning frameworks based on TensorFlow, and PyTorch on large-scale on-prem or cloud infrastructures.
  • Strong background in modern and advanced C++ concepts.
  • Strong Scripting Skills in Bash, Python, or similar.
  • Good communication with the ability to write clean, efficient, and well-documented code.

Team Collaboration

  • Strong communication skills and ability to work effectively in a cross-functional team setting.
  • Comfortable collaborating with diverse team members (developers, testers, domain experts) and conveying technical ideas clearly.

Adaptability

  • A willingness to learn new technologies and adapt to evolving project requirements.
  • Enthusiasm for working in a dynamic, fast-changing environment where priorities may shift as the project grows.

Preferred Qualifications (Nice-to-Haves) Background

  • Experience working on projects involving scientific computing, simulations, or HPC applications.
  • Familiarity with parallel computing concepts or engineering simulations (CFD, FEA, etc.) can help in understanding the platforms context.

DevOps & CI/CD

  • Hands-on experience with DevOps tools and workflows.
  • Knowledge of setting up CI/CD pipelines using platforms like Azure DevOps, Jenkins, or GitHub Actions to automate build and deployment processes.

Containerization & Cloud

  • Experience with container technologies (Docker) and orchestration (Kubernetes) for deploying microservices is a plus.
  • Familiarity with cloud services or infrastructure (Azure, AWS, etc.) for scalable deployment environments.

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