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We are seeking an experienced Senior Data Science Engineer with 2 - 6 years of experience to join our innovative team. As a Machine Learning and Generative AI Specialist, you will play a critical role in developing and deploying advanced ML models and algorithms to drive data-driven decision-making processes.
Here are the key responsibilities and desired skills:
1. Algorithm Development:
o Design and implement machine learning algorithms for various applications, including natural language processing (NLP), recommendation systems, and predictive analytics.
o Leverage your expertise in deep learning and generative AI to create innovative solutions.
2. Data Processing and Analysis:
o Collect, preprocess, and analyze large-scale datasets.
o Apply statistical techniques and feature engineering to extract meaningful insights from data.
3. Model Training and Evaluation:
o Train and fine-tune ML models using Python and relevant libraries (e.g., TensorFlow, PyTorch).
o Evaluate model performance using appropriate metrics and iterate to improve accuracy and efficiency.
4. Deployment and Monitoring:
o Deploy ML models to production environments (e.g., cloud platforms such as Azure, AWS, or GCP).
o Monitor model performance, troubleshoot issues, and ensure robustness and reliability.
5. Collaboration and Communication:
o Collaborate with cross-functional teams, including data scientists, engineers, and product managers.
o Communicate results and insights effectively to technical and non-technical stakeholders.
Desired Skills:
Machine Learning: Strong knowledge of ML algorithms, including supervised and unsupervised learning.
Generative AI: Experience with generative models (e.g., GANs, VAEs) and their applications.
Python: Proficiency in Python for data analysis, model development, and scripting.
Cloud Platforms: Hands-on experience with Azure, AWS, or GCP for model deployment and scalability.
Natural Language Processing (NLP): Understanding of NLP techniques, sentiment analysis, and text generation.
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Date Posted: 29/04/2025
Job ID: 110160901