About this role
The team is seeking a Machine Learning Platform Engineer to join their team and play a pivotal role in architecting and scaling their next-generation ML platform. In this role, you will drive the design and implementation of secure, cloud-native infrastructure that supports the full ML lifecycle, from data ingestion to model monitoring.
Key Responsibilities:
- Design and implement scalable ML infrastructure solutions.
- Collaborate with cross-functional teams to deliver innovative and efficient solutions.
- Ensure security and compliance of the ML platform.
- Monitor and optimize model performance and infrastructure efficiency.
- Support data ingestion and preprocessing workflows.
- Stay updated with the latest trends in machine learning and cloud technologies.
Required Skills & Qualifications:
- Strong experience with cloud platforms (AWS, Azure, or Google Cloud).
- Proficiency in programming languages such as Python or Java.
- Experience with machine learning frameworks (TensorFlow, PyTorch, etc.).
- Knowledge of containerization and orchestration tools (Docker, Kubernetes).
- Familiarity with data engineering and ETL processes.
- Excellent problem-solving and communication skills.
Experience:
- 5-8 years of relevant experience in machine learning and cloud infrastructure.
What we offer:
- Opportunity to work on cutting-edge technology in a collaborative environment.
- Professional growth and development opportunities.
- A dynamic and inclusive workplace culture.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.