Artificial Intelligence Engineer

1 week ago

Gurgaon, Haryana, India OnGrid Full time

We are looking for a motivated SeniorAI Engineer with experience in building high-performing, scalable, enterprise-grade applications, to join us, driving this vision, and taking it to a larger scale.

If you are a visionary, always on the lookout for the right solutions, and a technology geek, constantly seeking to learn and improve your skill set, then you are the type of person we are looking Collaborate with product and tech teams to manage and innovate AI strategy and R and D.

- Contribute to impactful AI use cases for internal and client applications.

- Develop AI/ML solutions for complex problems, maintaining ethical standards.

- Conduct research in fields like computer vision, NLP, Gen AI, and deep learning.

- Integrate and refine AI models in production systems using live A Bachelor's or Master's degree in Computer Science or a related field.

- Specialization in Data Science, Machine Learning, or Artificial Intelligence is a plus.

- A minimum of 3+ years of hands-on experience in solving real-world AI challenges, with a focus on areas such as Computer Vision, Deep Learning, Object Detection, Natural Language Processing (NLP),

Generative AI, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and AI agents.

- Strong proficiency in Python programming, with experience in frameworks like Django and Flask; knowledge of Java is advantageous.

- Familiarity with Microservices Architecture is a plus.

- Experience with cloud platforms (AWS, Azure, or Google Cloud) is desirable.

Technical Expertise

- Vision Models: Experience with vision models such as YOLO, ResNet, and OCR for real-time object detection, image classification, and text detection.

- Generative AI and LLMs: Expertise in generative AI models and large language models (LLMs) such as Claude, LLaMA, Qwen, Mistral, etc., as well as experience with multimodal models and AI-agent

frameworks.

- Proficient in implementing Retrieval-Augmented Generation (RAG) and working with open-source models from platforms like Hugging Face, Robo Flow, etc.

- AI Frameworks and Tools: Proficiency in using frameworks and libraries such as TensorFlow, PyTorch, LangChain (LangGraph, LangSmith), PydanticAI, OpenCV, Django, Flask, Postman, Docker, Swagger, AWS, and GCP.

- Accelerated Computing: Strong understanding of GPU-accelerated training, fine-tuning, and inference, with experience on platforms such as AWS, GCP, or in-house infrastructure.

- Production Deployment: Expertise in deploying, fine-tuning, and scaling AI models in production

environments, ensuring system reliability and high availability.

- Advanced AI Knowledge: In-depth understanding of convolutional neural networks, transformer architectures, vector databases, and data preparation pipelines

(ref:hirist.tech)

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