onsite

Python AI/ML Engineer – Computer Vision & NLP

The Python AI/ML Engineer will design and develop AI models for computer vision and natural language processing, utilizing the latest YOLO versions and integrating OpenAI APIs. This role involves optimizing model performance, processing large datasets, and collaborating with cross-functional teams to deploy AI solutions in production.

About the role

Key Responsibilities

Design and develop AI models for image recognition, object detection, and text understanding.
Work with the latest YOLO versions (v6, v7, v8) for real-time object detection and tracking.
Build and fine-tune CNNs and other deep learning architectures for computer vision tasks.
Integrate OpenAI APIs (ChatGPT, Whisper, DALL·E, etc.) for NLP, generative AI, and automation workflows.
Process and analyze large-scale datasets including images, videos, and text.
Collaborate with cross-functional teams such as data scientists, product managers, and software engineers.
Optimize model performance for accuracy, speed, and efficiency.
Stay current with advancements in machine learning, computer vision, and natural language processing.

Required Skills & Experience

4+ years of hands-on experience in AI/ML engineering.
Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, OpenCV, Scikit-learn.
Practical experience with YOLO (v6/v7/v8) and other real-time detection models.
Deep understanding of CNNs, transformers, and modern deep learning architectures.
Strong understanding of model quantization, optimization, and implementation of pre- and post-processing pipelines for deep learning models.
Experience handling large datasets and preparing high-quality annotations for training and evaluation.
Expertise in model conversion and optimization based on hardware.
Hands-on experience with OpenAI tools & APIs for NLP and generative AI.
Solid skills in image preprocessing, augmentation, and annotation pipelines.
Familiarity with NLP tasks including sentiment analysis, NER, and text summarization.
Experience deploying models using Docker, REST APIs, or cloud platforms (AWS/GCP/Azure) in production environments.
Strong problem-solving, debugging, and analytical abilities.

Preferred Qualifications

Knowledge with LLaMA, Stable Diffusion, or other generative AI frameworks.
Experience of MLOps tools such as MLflow, Weights & Biases, or Kubeflow.
Exposure to OCR tools like Tesseract or EasyOCR.
Prior experience working in AI product development or startups.

Education

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

About the role

Key Responsibilities

Design and develop AI models for image recognition, object detection, and text understanding.
Work with the latest YOLO versions (v6, v7, v8) for real-time object detection and tracking.
Build and fine-tune CNNs and other deep learning architectures for computer vision tasks.
Integrate OpenAI APIs (ChatGPT, Whisper, DALL·E, etc.) for NLP, generative AI, and automation workflows.
Process and analyze large-scale datasets including images, videos, and text.
Collaborate with cross-functional teams such as data scientists, product managers, and software engineers.
Optimize model performance for accuracy, speed, and efficiency.
Stay current with advancements in machine learning, computer vision, and natural language processing.

Required Skills & Experience

4+ years of hands-on experience in AI/ML engineering.
Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, OpenCV, Scikit-learn.
Practical experience with YOLO (v6/v7/v8) and other real-time detection models.
Deep understanding of CNNs, transformers, and modern deep learning architectures.
Strong understanding of model quantization, optimization, and implementation of pre- and post-processing pipelines for deep learning models.
Experience handling large datasets and preparing high-quality annotations for training and evaluation.
Expertise in model conversion and optimization based on hardware.
Hands-on experience with OpenAI tools & APIs for NLP and generative AI.
Solid skills in image preprocessing, augmentation, and annotation pipelines.
Familiarity with NLP tasks including sentiment analysis, NER, and text summarization.
Experience deploying models using Docker, REST APIs, or cloud platforms (AWS/GCP/Azure) in production environments.
Strong problem-solving, debugging, and analytical abilities.

Preferred Qualifications

Knowledge with LLaMA, Stable Diffusion, or other generative AI frameworks.
Experience of MLOps tools such as MLflow, Weights & Biases, or Kubeflow.
Exposure to OCR tools like Tesseract or EasyOCR.
Prior experience working in AI product development or startups.

Education

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.