Advanced Python Machine Learning Development
Budget: $25 – $50 USD
Role Overview:
We’re looking for a ML Developer to drive the design, development, and delivery of advanced machine learning solutions. The ideal candidate is not just a strong individual contributor but also a technical leader capable of setting direction, mentoring team members, and ensuring that ML initiatives align with business goals. Competitive ML experience (e.g., Kaggle, benchmarks) is a strong plus.
What does day-to-day look like:
Own end-to-end DS/ML solution development — from data pipelines and model design to deployment and monitoring.
Translate business objectives into robust ML architectures that accurately capture business logic and context.
Collaborate cross-functionally with Product, Engineering, and Business stakeholders to define problem statements and success metrics.
Evaluate and optimize models for performance, scalability, and accuracy using state-of-the-art techniques.
Stay current with advancements in AI/ML research and apply relevant innovations to improve outcomes
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Statistics, or a related quantitative field.
4+ years of hands-on DS/ML development experience,
Proficiency in key DS/ML areas and frameworks:Supervised and Unsupervised Learning Time-Series Forecasting Natural Language Processing (NLP) Computer Vision (CV) Statistical Modeling and Inference
Expertise in Python and core libraries (Pandas, NumPy, Scikit-learn, etc.).
Ability to understand and apply different models to real-world use cases
Strong understanding of data preprocessing, feature engineering, model tuning, and evaluation metrics.
Proven ability to design scalable, production-grade ML systems.
Preferred Qualifications:
Proven expertise in Deep learning (e.g., convolutional neural networks, recurrent neural networks, transformers).
Experience with cloud data platforms (Databricks, AWS, etc.)
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
Experimenting with new technologies and frameworks based on Research papers published in top conferences and journals
Work in a fully remote environment.
We’re looking for a ML Developer to drive the design, development, and delivery of advanced machine learning solutions. The ideal candidate is not just a strong individual contributor but also a technical leader capable of setting direction, mentoring team members, and ensuring that ML initiatives align with business goals. Competitive ML experience (e.g., Kaggle, benchmarks) is a strong plus.
What does day-to-day look like:
Own end-to-end DS/ML solution development — from data pipelines and model design to deployment and monitoring.
Translate business objectives into robust ML architectures that accurately capture business logic and context.
Collaborate cross-functionally with Product, Engineering, and Business stakeholders to define problem statements and success metrics.
Evaluate and optimize models for performance, scalability, and accuracy using state-of-the-art techniques.
Stay current with advancements in AI/ML research and apply relevant innovations to improve outcomes
Required Qualifications:
Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Statistics, or a related quantitative field.
4+ years of hands-on DS/ML development experience,
Proficiency in key DS/ML areas and frameworks:Supervised and Unsupervised Learning Time-Series Forecasting Natural Language Processing (NLP) Computer Vision (CV) Statistical Modeling and Inference
Expertise in Python and core libraries (Pandas, NumPy, Scikit-learn, etc.).
Ability to understand and apply different models to real-world use cases
Strong understanding of data preprocessing, feature engineering, model tuning, and evaluation metrics.
Proven ability to design scalable, production-grade ML systems.
Preferred Qualifications:
Proven expertise in Deep learning (e.g., convolutional neural networks, recurrent neural networks, transformers).
Experience with cloud data platforms (Databricks, AWS, etc.)
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
Experimenting with new technologies and frameworks based on Research papers published in top conferences and journals
Work in a fully remote environment.