ML Engineer
Tasks
- Build scalable training and inference pipelines
- Collaborate with product and analytics teams to define success metrics
- Deploy ML solutions via batch jobs or APIs using Docker and cloud platforms
- Design, develop, and deploy machine learning models
- Develop and refine value prediction signals such as LTV and conversion probability
- Improve recommenders and ranking models using offline and online evaluation techniques
- Own end-to-end ML projects including data exploration modeling deployment and monitoring
- Share knowledge through code reviews documentation and mentoring
Perks/Benefits
- Conference support
- Fully remote
- Health insurance reimbursement
- Language courses discount
- Paid vacation
- Recognition system
- Referral bonuses
- Training reimbursement
- Wellness days
- Workspace support
Skills/Tech-stack
AWS | Azure | Docker | GCP | ML algorithms | Model Deployment | Model Evaluation | Monitoring | NumPy | Pandas | Python | Ranking algorithms | Recommender Systems | SQL | Scikit-learn
Education
N/A
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