AI Engineer Data and AI

Engineering - Software & QA 7 months ago
Employment Information

Job description

  • If you're passionate about Generative AI, LLMs, and cutting-edge technology, and you enjoy building high-impact solutions, wed love to hear from you! As an AI Engineer on the Data and AI team, you will:

  • Collaborate with leadership to understand the vision, scope, and requirements for the enterprise platform

  • Help design and develop a smart, AI-driven platform that guides and optimizes projects with real-time intelligence

  • Work hands-on with the latest technologies like LLMs (Large Language Models) and Generative AI to build transformative tools

  • Assist in the integration of the platform with existing organizational systems, ensuring seamless functionality

  • Contribute to building scalable, reliable, and high-performance software solutions

  • Participate in peer reviews and champion code quality within the team

 

What do we expect

  • 3+ years of experience in MLE/MLOps/AI Engg

  • Experience working in LLMs, Generative AI, or similar AI technologies

  • Proficient in backend development using Python (Django/Flask) or similar technologies

  • Good understanding of APIs and microservices architecture

  • Ability to collaborate with cross-functional teams and work in a fast-paced environment

  • Passion for learning and applying new technologies to solve complex problems

  • You are important to us, lets stay connected!

  • Every individual comes with a different set of skills and qualities so even if you dont tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow

  • We are an equal opportunity employer

  • Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire

 

 

Skills
Software Development Life Cycle (SDLC) Programming Languages (e.g., Java, Python, C++) Software Testing (Manual & Automated) Quality Assurance Processes Debugging & Troubleshooting Test Automation Tools (e.g., Selenium, QTP) Version Control (e.g., Git) Continuous Integration & Deployment (CI/CD) Requirements Analysis
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