AI/ML Engineer

Job Description :

Key Responsibilities :

- Research, evaluate, and benchmark open-source models for classification, detection, and annotation tasks across text, audio, image, and video.

- Fine-tune and optimize models for accuracy, latency, and resource efficiency on real-world datasets.

- Build and maintain inference pipelines and APIs (using FastAPI, TorchServe, or Triton) for seamless integration with backend services.

- Collaborate with backend and data teams to design data flows for training, testing, and evaluation.

- Perform exploratory analysis and visualization to understand dataset quality and model behavior.

- Define and track evaluation metrics to continuously measure model performance and reliability.

- Contribute to early training pipelines, experiment tracking, and data versioning initiatives.

- 3- 5 years of experience in applied machine learning or AI engineering.

- Strong programming skills in Python, with hands-on experience in PyTorch or TensorFlow.

- Familiarity with data preprocessing and augmentation for text, audio, image, or video datasets.

- Experience running and profiling models for inference (GPU/CPU) using ONNX, TorchScript, or TensorRT.

- Working knowledge of FastAPI or similar frameworks for serving ML models.

- Practical understanding of Git, CI/CD, Docker, and Linux environments.

- Comfort working in cloud environments (AWS/GCP/Azure) and collaborating in agile, cross-functional teams.

- Experience with audio processing, speech recognition, or computer vision models (classification, segmentation, detection).

- Familiarity with annotation workflows and dataset QA.

- Understanding of model evaluation metrics (precision, recall, F1, mAP, AUC).

- Exposure to model optimization techniques (quantization, pruning, distillation).

- Experience with ML experiment tracking and dataset versioning tools (MLflow, DVC, Weights & Biases).

- Bonus : Knowledge of transformer-based