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Senior Machine Learning Engineer

2 months ago

London, Greater London, United Kingdom Talent Seed Full time
Job Title: Senior Machine Learning Engineer

Talent Seed is seeking a highly skilled Senior Machine Learning Engineer to join our team in Riyadh, KSA. As a key member of our AI platform, you will design, develop, and deploy advanced machine learning solutions across various domains, including NLP, LLMs, Recommender engines, and Anomaly detection.

Key Responsibilities:
  • Design and develop end-to-end machine learning solutions, from data preprocessing to service API creation.
  • Mentor junior team members and share knowledge on best machine learning and software engineering practices.
  • Establish and maintain robust communication channels with cross-functional teams to integrate machine learning solutions into other Unifonic products.
  • Develop and optimize highly confident machine learning algorithms and models, and create/expose service APIs using frameworks like Flask, FastAPIs, or other relevant frameworks.
  • Stay up-to-date with the latest machine learning research papers and AI trends.
  • Collaborate with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns in real-time, near-real-time, or batch processing mode.
  • Implement proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
  • Build scalable, maintainable machine learning services that handle thousands of requests per second and perform load tests to meet SLA.
Requirements:
  • 5+ years of relevant work experience as a Machine Learning Engineer.
  • ~3+ years of experience with Python.
  • ~ End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
  • ~ Ability to write world-class code in Python, considering best software engineering fundamentals.
  • ~ Solid experience in ML frameworks like NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
  • ~ Model deployment and reproducible research.
  • ~ Mastering data science requires skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
  • ~ Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modelling and optimization, evaluation metrics, classification, and clustering.