Accelerated Computing Specialist

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About the Role

We seek a driven Accelerated Computing Engineer to join our innovative team in Vellore. This

entry-level role offers a unique opportunity to work with advanced AI/ML models, accelerated

computing technologies, and cloud infrastructure while collaborating on cutting-edge research

and deployment projects.

You will work with a variety of state-of-the-art models such as BGE-Large, Mixtral, Gemma,

LLaMA, and Stable Diffusion, as well as other fine-tuned architectures, to solve real-world

computing challenges through advanced AI/ML infrastructure solutions.

Key Responsibilities

• Customer Interaction & Analysis: Work closely with customers to analyze technical

and business needs, translating them into robust, AI-driven solutions.

• Model Deployment & Optimization: Develop and deploy advanced AI/ML models such

as LLaMA, Mixtral, Gemma, and other GenAI models while optimizing their

performance for varied computing environments.

• Performance Testing & System Benchmarking: Execute advanced test scenarios and

performance benchmarks across AI/ML models and distributed systems to ensure

optimal performance.

• Infrastructure & Model Research: Research, configure, and maintain infrastructure

solutions (using tools like TensorRT and PyTorch) supporting our models and

accelerated computing workloads.

• AI/ML Model Integration: Support and deploy models such as Stable Diffusion, BGE,

Mistral, and custom fine-tuned models into end-to-end pipelines for AI/ML-driven

solutions.

• Automation & Process Improvements: Drive automation strategies to streamline

workflows, improve testing accuracy, and optimize system performance.

• Technical Liaison: Served as the technical bridge by collaborating with product

development teams, tracking customer feedback, and ensuring timely resolutions.

• Model Configuration & Troubleshooting: Create custom scripts, troubleshoot

advanced configurations, and support tuning efforts for AI/ML model customization.

Kanchipuram

Skills & Qualifications

Required Skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related

technical discipline.

• Strong foundational knowledge of AI/ML model deployment and cloud infrastructure.
• Proficiency with AI/ML frameworks & libraries, including PyTorch, TensorRT, and

Triton.

• Hands-on experience with deployment models such as LLaMA, Mixtral, Gemma, and

Stable Diffusion.

• Familiarity with distributed computing environments and orchestration tools like

Kubernetes.

• Proficiency in workflow automation, performance tuning, and large-scale system

debugging.

• Understanding of cloud computing technologies and infrastructure architecture, including

storage, networking, and computing paradigms.

Preferred Skills:

• Experience working with object storage technologies like AWS S3, Azure Blob

Storage, and MinIO.

• Familiarity with advanced AI/ML model frameworks such as Gemma-2b,

Mixtral-8x7b, Mistral-7b-instruct, and other fine-tuned AI models.

• Expertise in GPU configuration and tuning for AI/ML workloads, including drivers and

machine learning optimization strategies.

• Familiarity with serverless computing and Function as a Service (FaaS) concepts.
• Experience with infrastructure as code (IaC) and performance benchmarking

methodologies.