ML Engineer
Tasks
- Assign projects and manage team workloads
- Build end-to-end ML pipelines
- Coach and mentor team members
- Collaborate with cross-functional teams
- Design scalable automated data processes
- Develop machine learning models
- Improve model accuracy after delivery
- Integrate AI ML solutions with business requirements
- Lead AI ML project delivery lifecycle
- Manage responsible AI compliance
- Monitor model performance
- Oversee project milestones and governance
- Perform model validation and testing
- Train validate and deploy models
Perks/Benefits
- Annual leave
- Digital learning platforms
- Employee assistance program
- Flexible working arrangements
- Learning & development opportunities
- Life insurance
- Medical coverage
- Mental health resources
- Parental/maternity leave
- Resilience training
- Retirement savings plan
- Sabbatical
- Volunteering leave
Skills/Tech-stack
Classification | Clustering | Computer Vision | Deep learning | DevOps | Django | GitHub | Language Models | Language Processing | Large Language Models | Machine Learning | Model Validation | Natural Language | Natural Language Processing | Optimization | PostgreSQL | Prompt engineering | PyTorch | Python | Relational databases | Responsible AI | Supervised Learning | TensorFlow | Unsupervised Learning
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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