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Senior Machine Learning Engineer
2 months ago
Position Overview:
Bonfy.AI is seeking a highly skilled and motivated Senior Machine Learning Engineer to join our dynamic team. The ideal candidate will play a pivotal role in developing, deploying, and optimizing machine learning models that scale across diverse applications. This role requires a deep foundation in machine learning, data science, and software development. You will work on cutting-edge technologies and directly impact the growth and success of our startup by driving innovations that are robust, efficient, and scalable for our needs.
Responsibilities:
Design, implement, and optimize machine learning models across domains such as natural language processing, classification, anomaly detection, and more.
Develop and maintain end-to-end machine learning pipelines, from data gathering and preprocessing to model training, testing, and deployment.
Stay current with the latest developments in machine learning, natural language processing, and artificial intelligence and assess new tools and frameworks for their applicability to ongoing projects.
Ensure the scalability and reliability of machine learning systems through continuous evaluation, tuning, and performance benchmarking.
Collaborate closely with data engineers and software developers to ensure seamless integration and scalability of models in production environments.
Provide mentorship to junior team members and contribute to shaping our technology strategy and roadmap.
Technical Requirements:
BSc. or MSc. in Computer Science, Data Science, Machine Learning, or related fields.
Minimum of 5 years of hands-on experience in developing commercial-grade solutions (or equivalent) in machine learning and artificial intelligence.
Proven expertise in designing, training, and deploying machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn.
Strong programming skills in Python and familiarity with ML libraries. Solid understanding of algorithms, data structures, and software engineering principles.
Experience in scaling models for production use cases, emphasizing performance optimization and robustness.
Familiarity with cloud platforms such as AWS, Google Cloud, or Azure, including AI/ML services.
Strong knowledge of data science principles, including statistical analysis and evaluation metrics for machine learning tasks.
Additional Requirements:
Applicants must have legal authorization to work in the United States.
Applicants must be able to work in a hybrid mode at our office located in Mountain View, California.
