About the job

We are seeking a highly skilled and motivated AI Software Engineer with 2+ years of experience in Machine Learning (ML), Computer Vision (CV), Natural Language Processing (NLP), and cutting-edge AI technologies. The ideal candidate will have a strong foundation in AI model development, software engineering, and deep learning architectures and a passion for solving complex real-world problems.

Key Responsibilities:

• Design, develop, and optimize machine learning models for Computer Vision (CV) (Mostly), NLP, and AI applications such as image recognition, object detection, OCR, speech processing, and generative AI.
• Develop and implement AI-powered pipelines, including data preprocessing, feature extraction, model training, and deployment for large-scale applications.
• Leverage recent AI advancements, including Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Agentic AI frameworks to build state-of-the-art AI solutions.
• Deploy and Monitor ML models to production using cloud platforms (AWS, GCP, Azure) or on-premise AI infrastructure with containerization tools like Docker and Kubernetes.
• Optimize deep learning models for performance, efficiency, and scalability, utilizing TensorFlow, PyTorch, ONNX, and Hugging Face Transformers.
• Collaborate with cross-functional teams to integrate AI solutions into real-world applications, ensuring alignment with business objectives.
• Monitor, evaluate, and fine-tune deployed models, ensuring high accuracy, robustness, and adaptability in dynamic environments.
• Stay up-to-date with AI research trends, including multi-modal AI, generative AI (GANs, diffusion models), reinforcement learning, and autonomous AI agents.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Data Science, or a related field.
• Strong programming skills in Python and experience with ML/AI frameworks such as TensorFlow, PyTorch, OpenCV, and Hugging Face Transformers.
• Proficiency in data manipulation and preprocessing tools such as Pandas, NumPy, Scikit-learn, and NLTK/spaCy for NLP tasks.
• Hands-on experience with Computer Vision techniques, including object detection (YOLO, Faster R-CNN), segmentation, and facial recognition.
• Experience in NLP applications, such as LLMs, chatbot development, Named Entity Recognition (NER), and text-to-image generation.
• Familiarity with LLMs, RAG, Vector Databases (e.g., FAISS, Milvus, pgvector), and knowledge retrieval mechanisms.
• Experience deploying AI models using APIs, serverless computing, and edge AI platforms.
• Knowledge of MLOps principles, including CI/CD for ML pipelines, model versioning, and performance monitoring.
• Strong problem-solving skills and ability to work in a fast-paced, AI-driven environment.

Preferred Qualifications:

• Experience with big data processing frameworks such as Apache Spark, Dask, or Ray.
• Hands-on knowledge of GANs, Stable Diffusion, and transformer-based architectures (e.g., BERT, GPT, CLIP).
• Proficiency in CUDA programming, TensorRT optimization, or hardware acceleration techniques.
• Experience with speech-to-text (ASR), text-to-speech (TTS), and generative AI applications.
• Familiarity with edge AI deployments for mobile and embedded systems (e.g., TensorFlow Lite, OpenVINO).
• Understanding of LLM fine-tuning, prompt engineering, and AI alignment techniques.
• Contributions to open-source AI projects or research publications in ML/CV/NLP fields.