Tiger Analytics | Generative AI Engineer

4 days ago


Bengaluru, India Tiger Analytics Full time
AI Engineer – Data and AI

Experience :3.5 – 11 YearsImmediate or 30 daysLocation: Chennai, Bengaluru, and Hyderabad

About Role:

We’re looking for a talented and driven AI Engineer to join a meaningful internal strategic initiative and also to contribute to solving complex AI/ML problems for our clients. You'll be working closely with senior leadership, including one of our founders, to help build an innovative enterprise platform for the organization. This platform will act as a digital twin of our existing systems—an intelligent bot/ Platform that provides real-time insights on what needs to be done and how to do it.If you're passionate about Generative AI, LLMs, and cutting-edge technology, and you enjoy building high-impact solutions, we’d 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.

Skills Preferred:Mandatory Skill:3-7+ 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.Python Proficiency:

Good experience with Python, including libraries such as TensorFlow, PyTorch, Scikit-learn, or Pandas. Dive into problem-solving approaches in coding challenges or specific projects they have handled.Deployment :

Good experience in deploying models to production, whether through microservices, APIs, or containers (Docker, Kubernetes). Discuss specific challenges they faced and how they ensured model robustness.Microservices & APIs:

Good understand on Microservices & APIs on Python framework.Cloud Expertise:

Good understanding with at least one cloud platform (AWS, Azure, Google Cloud, etc.) and be open to learning others.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.Good to have Skill :Methodology:

Good understanding on Agile & Scrum MethodologyPySpark :

Good understanding on PySpark Programming for data Cleaning & Data PreparationProject Exposure:

Good understanding on multiple project implementation experienceConcurrency and Parallelism: :

Good Understanding and application of concurrency and parallelism concepts.



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