Role Overview:
We are seeking skilled and experienced ML Developers to join our innovative team.
The ideal candidate will have strong hands-on ML experience with the ability to understand complex data models and translate business requirements into efficient solutions that capture business context accurately.
Participation in machine learning competitions is a strong plus.
What does day-to-day look like:
- Develop and maintain ML solutions, including data pipelines, model training, evaluation, and optimization.
- Collaborate with business stakeholders to gather and clarify requirements.
- Translate business requirements into ML code that accurately reflects business logic.
- Write efficient, maintainable, and well-documented ML solutions.
- Participate in code reviews and follow established development standards.
- Effectively analyze and select the best algorithms, optimize ML solutions for performance improvement and accuracy.
- Create and maintain technical documentation for developed solutions.
- Support testing activities and resolve data-related issues.
Required Qualifications:
- 3+ years of hands-on ML development experience.
- Proficiency in at least some of the ML areas and frameworks, including:
- Supervised learning (classification, regression, …)
- Unsupervised learning (clustering, anomaly detection, …)
- Time-series analysis
- Natural Language Processing (NLP)
- Computer Vision (CV)
- Statistical modeling
- Ability to understand and apply different models to real-world use cases
- Hands-on experience with DS and ML solutions in production environments
- Strong understanding of data cleaning and wrangling, feature engineering, model optimization, and evaluation metrics
- Proficiency in Python and its common data science libraries (e.g., Pandas, NumPy, Scikit-learn)
Preferred Qualifications:
- Proven expertise in Deep learning (e.g., convolutional neural networks, recurrent neural networks, transformers).
- Experience with cloud data platforms (Databricks, AWS, etc.)
- Knowledge of MLOps principles and tools for model deployment and monitoring.
- Hands-on experience with PySpark and Databricks Platform.
- Stay up-to-date with the latest advancements in machine learning and artificial intelligence.
- Bonus: Experience and knowledge in Kaggle competitions and Benchmarks, such as MLEBench