Software Developer - Senior

Max Rate: $85/hr on w2


AMD


12+ month contract
The position is hybrid in San Jose, CA
Interview Process: Onsite or MS Teams


Top 3-5 Must Have Skills for this role:


- Strong skills in Python and data analysis libraries (Pandas, NumPy, SQL).
- Demonstrable experience or strong projects in LLM/RAG development.
- Strong proficiency in agentic LLM Libraries/Technologies like LangChain, LangGraph, AutoGen, CrewAI, etc.
- Familiarity with RL, techniques for fine-tuning LLMs (e.g., LoRA), and other emerging ML methodologies.


Responsibility
• Play key role in design, development, and deployment of large-scale high-performance enterprise ready agent frameworks and tools.
• Collaborate with engineering team to understand specific needs and challenges of chip design and ensure our agent platform is well-suited to these needs
• Develop and optimize retrieval and generation algorithms for enterprise data (text, code, and images) to build advanced AI applications.
• Design, implement, test, and continuously optimize end-to-end RAG pipelines, including data parsing, ingestion, prompt engineering, and chunking strategies.
• Collect & organize training / fine-tuning data and help build domain specific large language models.
• Optimize infrastructure for performance, scalability, and reliability, and ensure secure and efficient management of data.
• Stay ahead by engaging with the latest advancements in machine learning and AI to create state-of-the-art solutions.


Qualifications
• BS or MS Degree in Electrical Engineering, Computer Science/Engineering, or a related discipline (or equivalent experience).
• 5+ years of proven industry experience
• Skilled at rapidly taking products from concept to launch and scaling them massively by performance tuning and optimizing complex, globally distributed systems
• Demonstrable experience or strong projects in LLM/RAG development.
• Strong skills in Python and data analysis libraries (Pandas, NumPy, SQL).
• Strong proficiency in agentic LLM Libraries/Technologies like LangChain, LangGraph, AutoGen, CrewAI, etc.
• Familiarity with RL, techniques for fine-tuning LLMs (e.g., LoRA), and other emerging ML methodologies.
• Optimize inference and infrastructure for low-latency, cost-effective operation (vLLM/TGI/Triton, batching, caching, quantization) on GPU/accelerators; support on-prem/VPC deployments with enterprise security controls.
• A proactive approach to problem-solving and a willingness to acquire new skills and knowledge as needed to achieve results.