Machine Learning Engineer

As an ML Engineer, you will play a crucial role in designing, developing, training, and deploying machine learning models. Your responsibilities will include ensuring that AI capabilities meet production-grade standards, are robust, and seamlessly integrated into the company's software stack. Your tasks will involve designing, building, and training machine learning models using state-of-the-art frameworks, translating AI product requirements into scalable model architectures, packaging models as APIs/microservices for seamless integration into products, setting up CI/CD pipelines for automated model training and release, as well as evaluating model performance and managing versioning. The ideal candidate for this role should have proficiency in languages such as Python and SQL, as well as hands-on experience of 3-6 years in applied machine learning and deploying models in production environments. Additionally, familiarity with frameworks like PyTorch, TensorFlow, and Hugging Face Transformers is essential. Desirable skills for this role include expertise in tools like MLflow, Docker, FastAPI, and GitHub Actions, along with experience in deployment platforms such as GCP Vertex AI and AWS SageMaker. Joining our team will provide you with the opportunity to collaborate with a diverse and experienced team, contribute to the growth stories of renowned brands, and benefit from a professional growth roadmap. You can expect real-time mentorship and guidance from industry leaders, a supportive work environment that invests in your career development, and various employee benefits such as competitive salary, flexible work-life balance, paid time off, learning & development bonuses, health coverage, rewards & recognitions, and ongoing training programs. If you are a passionate and talented individual looking to join a team of artists, geeks, strategizers, and writers, we encourage you to apply. Our workplace fosters a culture of inclusivity, creativity, and excellence, allowing you to be yourself and do exceptional work while enjoying onsite opportunities and recognition for open-source contributions.,