Machine Learning Engineer (Generative AI & LLMs)-Austin, Tx or Sunnyvale, CA- W2 only--No Sponsorship-

Role-Need Machine Learning Engineer (Generative AI & LLMs) Profile

Location-Austin, Tx or Sunnyvale, CA- Onsite from Day 1

Duration :12+ Months

Job Description:

• The Machine Learning Engineer is responsible for designing, developing, and deploying machine learning solutions with a strong focus on Generative AI and Large Language Models (LLMs).
• The role involves building end-to-end AI workflows, developing LLM-powered applications, performing prompt engineering, optimizing model outputs, and supporting model migration and deployment.
• The engineer works closely with stakeholders to understand problem statements, identify effective solutions, and deliver reliable, high-quality AI results.

Key Responsibilities:

• Develop and maintain machine learning and LLM-based applications using Python
• Design and implement end-to-end workflows for LLM use cases, from problem understanding to solution delivery
• Build applications for NLP tasks such as translation, summarization, and text processing using LLMs
• Perform prompt engineering, including prompt design, testing, iteration, and optimization for improved outputs
• Write clean, modular, and reusable Python functions and code
• Optimize models, prompts, and workflows for better performance, accuracy, and reliability
• Analyze problem statements and identify effective AI-driven solutions
• Support model migration across environments or platforms
• Assist with model deployment and integration into applications or systems
• Use Git for version control and collaborative development
• Document solutions, provide regular updates, and communicate results clearly
• Required Skills & Competencies
• Proficiency in Python
• Strong understanding of Machine Learning concepts and methodologies
• Hands-on experience with Generative AI and Large Language Models (LLMs)
• Experience in Natural Language Processing (NLP)
• Knowledge of Prompt Engineering techniques and best practices
• Familiarity with model migration and deployment processes
• Experience with Git and version control systems
• Strong problem-solving, analytical, and communication skills
• Preferred / Additional Skills
• Exposure to multiple LLM frameworks, APIs, or platforms
• Understanding of ML or LLM optimization techniques

Familiarity with production ML workflows or MLOps concepts