Machine Learning Engineer

Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Over 5 years of experience in a development team utilizing agile methodologies and collaborating with technologists, creatives, project managers, and strategists.
Skills and Expertise
Well-versed in software development best practices, including version control systems (e.g., Git) and agile methodologies.
Proven ability to make well-reasoned design decisions and tradeoffs in areas of expertise.
Passionate about discovering new technologies, industry trends, and best practices, and enjoys sharing knowledge with others.
Technical Proficiency
Excellent problem-solving skills and keen attention to detail.
Strong communication and collaboration skills, capable of working effectively in a team environment.
Extensive experience in Python and a solid grasp of computer science fundamentals such as object-oriented programming, data structures, algorithm design, problem-solving, and complexity analysis.
Experience using coding assistants (e.g., Copilot) to enhance daily tasks.
Proficient in popular Python web frameworks such as Django, Flask, or FastAPI.
Additional Expertise
Understanding of machine learning concepts and techniques, with a desire to further develop ML skills.
Experience in data manipulation and feature engineering using tools like NumPy, pandas, and Jupyter Notebook.
Bonus if you have experience with Google Cloud Platform, TensorFlow, PyTorch, GCP Vertex AI, Hugging Face, LangChain, AWS Bedrock, PostgreSQL, MongoDB, MySQL, or BigQuery.

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