Job
Description
JOB DESCRIPTION Designation: ML Operations Engineer Location: Hyderabad, India Work Mode: Office Reporting to: Principal Data Scientist Job Overview: At Foundation AI, As an ML Operations Engineer, you will design, develop, and maintain machine learning pipelines. You will work with structured and unstructured data. Your primary responsibility is to streamline the data science pipeline by automating the steps from Data gathering to Model deployment. Lifelong learning is crucial for long-term success, and we encourage you to stay current with the latest research by visiting conferences and sharing your knowledge throughout the enterprise. Responsibilities: You take responsibility for setting up maintainable and reliable ML pipelines on which our data scientists train the models. As part of an agile team, your ideas will be heard and impact the decision-making process. With our goal to invent for life, you will work on solutions that are both innovative and ethical. You will collaborate with ML engineers, data scientists, software developers, and DevOps engineers to have a real-world impact. Optimize the cost and latency of the services in production. Deploy the machine learning models in a scalable manner by utilizing the model-serving tools Skills and Tools: 3+ years of experience with Python, Linux skills, and machine learning principles 3+ years of experience in building and operating ML pipelines and data platforms in production 3+ years of experience in API design, distributed architectures, and orchestration of microservices Experience with container-based deployments (e.g. Docker, Kubernetes) Experience deploying deep learning models to a production environment Model lifecycle management (e.g. MLflow, KubeFlow) - 2+ years of experience in Workflow automation (e.g. Airflow) - 2+ years of experience in Version control of model files (like DVC) - 2+ years of experience in Exposure to Deep Learning frameworks, such as PyTorch, TensorFlow, etc - 2+ years of experience Experience working with the Cloud (AWS, Azure, GCP, etc.) - 2+ years of experience Personality and Working Practice: motivating attitude, profound communication, strong interpersonal skills, structured and analytical Experience in using Serving tools (RayServe, KServe) - 1 year(s) experience Experience in building and maintaining LLM pipelines - 1 year(s) experience Education: Bachelor's degree in Computer Science, Engineering, related field, or equivalent work experience. Our Commitment: At Foundation AI, we're committed to creating an inclusive and diverse workplace. We value equal opportunity and affirmative action principles, giving everyone an equal chance to succeed. We're dedicated to offering equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status. Upholding these values and adhering to applicable laws is paramount to us. For any feedback or inquiries, please contact us at careers@foundationai.com Learn more about us at www.foundationai.com
