Python developer for AI-ML

LLM - Python for Machine Learning

YoE : 4+ years

Role Type: Remote

Start Date : Immediate

Compensation : 8-9 LPA

Skills : Python OR Python for ML,| Machine Learning OR PyTorch OR Keras OR Tensorflow OR Scikit-Learn

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.

Roles & Responsibilities:

•⁠ ⁠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:

•⁠ ⁠Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.

•⁠ ⁠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