At Iron Mountain we know that work, when done well, makes a positive impact for our customers, our employees, and our planet. That’s why we need smart, committed people to join us. Whether you’re looking to start your career or make a change, talk to us and see how you can elevate the power of your work at Iron Mountain.
We provide expert, sustainable solutions in records and information management, digital transformation services, data centers, asset lifecycle management, and fine art storage, handling, and logistics. We proudly partner every day with our 225,000 customers around the world to preserve their invaluable artifacts, extract more from their inventory, and protect their data privacy in innovative and socially responsible ways.
Are you curious about being part of our growth story while evolving your skills in a culture that will welcome your unique contributions? If so, let's start the conversation.
Required skill set:
● 0-4 years experience as a machine learning engineer/data scientist. (0-2 is suggested to be junior while 3-4 year experience is suggested to be intermediate level. However, interview performance will determine the level and is not limited by working years.)
● Strong DL for cases like image/audio/text classification.
● Strong NLP (LLM) knowledge on entity extraction. Multi-lingual LM and multi-modal LM experience are extremely preferred.
● Hands on experience on GenAI (LLM), and experts on prompt engineering.
● Machine learning pipeline knowledge and hands-on experience on Kubeflow or mlflow frameworks. This is highly desirable but not required.
● Strong Python knowledge is essential.
● Experience of training models with accelerators.
● knowledge and/or hands-on experience with performance tuning, like LORA etc, are desirable.
● Experience on deploying models and optimizing tradeoff among throughput, latency and cost, are desirable but not required.
● Exposure to MLOps / Data Engineering is highly desirable but not required.
Let our experts design a Professional CV for you.