Senior ML Engineer
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Job Description
Senior ML Engineer developing and training models for AI-driven automation projects at a leading data solutions firm. Collaborating cross-functionally and managing the full model lifecycle.
Responsibilities:
- Develop and train transformer-based models for text and image processing, ensuring high performance and scalability.
- Design and manage the full model lifecycle, from data preparation and model architecture to training, validation, deployment, and continuous monitoring.
- Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to build and implement AI-driven solutions that align with business objectives.
- Stay up to date with the latest advancements in AI and machine learning, incorporating cutting-edge techniques and technologies to enhance model effectiveness.
Requirements:
- Strong expertise in large-scale Neural Networks, Deep Learning, Fine Tuning, and Reinforcement Learning techniques, with a focus on real-world applications.
- Hands-on experience with GenAI projects and related frameworks, including RAG applications, vector databases, LangChain, LlamaIndex, and agentic frameworks.
- Advanced proficiency in Python and machine learning libraries, such as SciPy, Scikit-learn, TensorFlow, PyTorch, pyMC, and pgmpy.
- Practical experience with cloud computing platforms, preferably Azure, but also AWS or GCP.
- Deep understanding of the full ML lifecycle, with hands-on experience in MLOps and DataOps practices.
- Strong background in Probabilistic Graphical Models, including Bayesian Networks, Markov Random Fields, and Factor Graphs.
- Excellent problem-solving skills and keen attention to detail.
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