LLM - Python for Machine Learning - 2+

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