07 || ML Engineer (India)

Job Title: ML Engineer

Exp: - 2 to 5 years

Location: - Noida, Sector 63 (A Block)

Job Description

As a Machine Learning Engineer, you will work on designing, developing, and deploying machine learning models that leverage Computer Vision and Generative AI techniques. You will be responsible for building and improving AI systems that solve real-world problems, driving the next wave of innovation in our products and services.

Required Skills and Qualifications

2-5 years of hands-on experience in machine learning engineering with a focus on Computer Vision and Generative AI.

Strong knowledge of machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar.

Expertise in Computer Vision techniques, including image classification, object detection, segmentation, and tracking.

Hands-on experience with Generative AI models such as GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other deep learning-based generative models.

Solid understanding of computer vision libraries such as OpenCV, scikit-image, or similar.

Experience with model optimization techniques such as pruning, quantization, and knowledge distillation.

Strong programming skills in Python, with experience in data manipulation (e.g., pandas, NumPy), model training, and evaluation.

Knowledge of NLP, Deep Learning, and/or other AI fields.

Solid programming skills in Python, with experience in data manipulation, model training, and evaluation.

Familiarity with DevOps practices related to machine learning (CI/CD, version control, automated testing).

Familiarity with cloud platforms (AWS, GCP, or Azure) and deployment tools (Docker, Kubernetes, etc.).

Knowledge of reinforcement learning or other advanced AI techniques.

Experience with deploying models to production and managing model lifecycle.

Excellent problem-solving skills, analytical thinking, and a passion for innovation.

Strong communication skills to collaborate with cross-functional teams and explain complex AI concepts clearly.