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