AI/ML Engineer – Search
Fractional Jobs
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇮🇳 India
Visit company websiteJob Level
JuniorMid-Level
Tech Stack
DockerEC2NumpyPythonPyTorchTensorflow
About the role
- Build and extend backend services that power AI-driven media search and metadata enrichment
- Develop, integrate, and deploy AI/ML inference pipelines (embeddings, vision/audio models, transcription, background removal, etc.)
- Fine-tune and optimize computer vision and generative models (e.g., U²Net, BiRefNet, CLIP, Whisper, YOLO, diffusion models)
- Work with large datasets (100k–5M images): preprocessing, augmenting, and structuring for training/inference
- Contribute to building pipelines for tasks like background removal, inpainting/outpainting, banner generation, logo/face detection, and multimodal embeddings
- Integrate with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) for similarity and semantic search
- Collaborate with the engineering team to deploy scalable AI inference endpoints (Docker + GPU/EC2/SageMaker)
Requirements
- 2–3 Years
- Core Python (Required) – solid programming and debugging skills in production systems
- AI/ML Libraries – hands-on experience with PyTorch and/or TensorFlow, NumPy, OpenCV, Hugging Face Transformers
- Model Training/Fine-Tuning – experience fine-tuning pre-trained models for vision, audio, or multimodal tasks
- Data Handling – preprocessing and augmenting image/video datasets for training and evaluation
- Vector Search – familiarity with FAISS, Pinecone, or similar for embeddings-based search
- Comfortable with chaining or orchestrating multimodal inference workflows (e.g., image + audio + OCR → unified embedding
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonAI/MLcomputer visiongenerative modelsmodel trainingfine-tuningdata preprocessingdata augmentationmultimodal inferencedebugging