AI/ML Engineer

Job highlights

• Experience with pre-trained multimodal models (CLIP,Whisper,ViT)

• Bachelor s in CS,AI,Data Science,or equivalent

• Preferred Skills

• The Associate AI/ML Engineer supports the development of machine learning and multimodal

• capabilities across text, image, audio, and video. This role focuses on data engineering tasks,

• implementing baseline models, and assisting senior engineers in building production-ready AI features for media workflows such as content tagging, speech transcription, image understanding, and personalized recommendations.

Detailed Responsibilities

Model Development & Research

• Implement baseline ML models for classification, regression, recommendation, and text analytics.
• Train small-scale multimodal models using datasets containing images, audio, and video frames.
• Conduct experiments with OCR, ASR, TTS, object detection, and emotion/sentiment detection.

Data Preparation & Feature Engineering

• Clean and preprocess structured/unstructured media data (transcripts, videos, images).
• Extract features from audio/video using libraries like OpenCV, ffmpeg, librosa.
• Support dataset creation for multimodal tasks (frame extraction, audio segmentation).

Pipeline Development

• Assist in building training and evaluation pipelines (data loaders, augmentation pipelines).
• Support deployment of inference APIs using FastAPI/Flask.

Testing, Documentation, and Code Quality

• Write unit tests, maintain notebooks/scripts, and ensure code hygiene.
• Document workflows, model behaviors, and experiment results.

Cross-functional Collaboration

• Work with senior ML engineers, data engineers, and media teams to support AI features.
• Assist in preparing demos, POCs, and reports.

Must-Have Skills

• Python, Pandas, NumPy, Scikit-learn.
• Basics of deep learning (CNNs/RNNs/Transformers).
• Familiarity with PyTorch/TensorFlow, OpenCV, librosa.
• Understanding of media formats: MP4, WAV, PNG/JPEG, subtitles.
• Exposure to cloud ML services (Azure Video Indexer, AWS Rekognition).

Preferred Skills

• Experience with pre-trained multimodal models (CLIP, Whisper, ViT).
• Basic understanding of embeddings and vector databases.
• Familiarity with data labeling and annotation tools.

Qualifications

• Bachelor s in CS, AI, Data Science, or equivalent.
• Internships or academic projects in machine learning or media AI.
• Could not find your suitable role above

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