Machine Learning Engineer

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Requirements:

• 4+ years of ML experience at a start-up or larger enterprise.
• 6+ months of experience with Large Language Models (LLMs) and Generative AI (GenAI) applications.
• Client delivery experience.
• Effective written and oral communications skills (C1/C2 - advanced/proficient level English is required).
• Bachelor’s degree in computer science, software engineering or related field.
• Experience with cloud environments (e.g., AWS, Azure, GCP).
• Experience with ML frameworks and libraries (TensorFlow, PyTorch, Keras, scikit-learn).
• Experience developing, deploying, and managing/monitoring models.
• Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture.
• Expertise in Object-Oriented Programming (OOP) principles and unit test-driven development methodologies.
• Advanced experience in NLP techniques and applications.
• Strong proficiency in Python programming.
• Familiarity with prompt engineering approaches and best practices.
• Knowledge of data structures, data modeling, and software architecture.
• Strong analytical and problem-solving skills, with ability to propose innovative solutions and troubleshoot issues.
• Ability to work independently and as part of a collaborative team in a fast-paced environment.

Responsibilities:

• Contribute to building and enhancing our Mechanized AI platform and AI-enabled products including mAI Modernize.
• Serve as ML SME on client projects as needed.
• Design ML systems.
• Research and implement appropriate ML algorithms and tools.
• Select appropriate datasets and data representation methods.
• Run ML tests and experiments.
• Perform statistical analysis and fine-tuning using test results.
• Train and retrain systems when necessary.
• Extend existing ML libraries and frameworks.
• Stay current with emerging technologies and ML best practices to continuously improve our methodologies and tools.