Machine Learning Engineer - Google Cloud Platform (3-12 yrs)

Responsibilities :

- Design, develop, and deploy high-performance deep learning models using PyTorch and Hugging Face Transformers.

- Experiment with various deep learning architectures and techniques to achieve optimal model performance.

- Preprocess, clean, and prepare large datasets for machine learning training.

- Train and fine-tune deep learning models on Google Cloud infrastructure, potentially utilizing distributed GPU compute.

- Integrate and deploy machine learning models into production environments using CI/CD pipelines (e.g , Terraform).

- Continuously monitor and evaluate model performance, identify areas for improvement, and iterate on the development process.

- Collaborate effectively with data scientists, software engineers, and product managers to bring machine learning solutions to life.

- Stay up-to-date with the latest advancements in deep learning research and best practices.

Qualifications :

- 5-12 years of experience in machine learning with a proven track record in deep learning model development and deployment.

- 2+ years of strong hands-on experience with PyTorch, Hugging Face Transformers, and deep learning concepts (optimizers, learning rate schedulers).

- Proficiency in Python programming language (4+ years of experience).

- Familiarity with cloud platforms, particularly Google Cloud Platform (GCP) services like GCS, BigQuery, Cloud Run, Cloud Build, and Pub/Sub (preferred).

- Experience with CI/CD pipelines and infrastructure automation tools (Terraform) is a plus.

- Strong analytical and problem-solving skills.

- Excellent communication and collaboration skills.

- A passion for learning and staying current with the latest advancements in machine learning