Remote Senior Machine Learning Engineer - Remote

Description:

• As a Senior Machine Learning Scientist at Zyte, you will drive the development and implementation of machine learning technologies that scale and optimize web data extraction.
• You will work on cutting-edge projects that involve both research and production-level development.
• Your role will include innovating using machine learning models to automate data extraction and contribute to internal systems, improving the quality, efficiency, and performance of the Zyte platform.
• Key responsibilities include leading the design, development, and deployment of machine learning models and algorithms for web data extraction and processing.
• You will collaborate closely with domain experts, cross-functional teams, and stakeholders to identify data requirements, define hypotheses, and guide experimentation.
• Your tasks will involve data collection, cleaning, preprocessing, and exploration to enable high-quality model training.
• You will suggest and conduct experiments aimed at improving the accuracy and efficiency of existing models and systems.
• Implementing machine learning model improvements in production, optimizing codebases, and enhancing tooling will be part of your responsibilities.
• Staying at the forefront of machine learning research, particularly in deep learning and large language models (LLMs), and applying innovative techniques to real-world problems is expected.
• You will provide mentorship and guidance to junior team members, promoting best practices in machine learning and software engineering.
• Contributing to the community through publications, talks, and open-source contributions is also part of the role.

Requirements:

• A deep understanding of machine learning algorithms and deep learning models (e.g., CNN, RNN, Transformers) is required.
• Experience working with large language models (LLMs) and applying them in production is necessary.
• Knowledge of data preprocessing, feature engineering, and model tuning is essential.
• You must have experience in deploying machine learning models at scale in production environments.
• Strong expertise in Python and machine learning libraries (e.g., PyTorch) is required.
• Knowledge of data structures, algorithms, and performance optimization techniques is necessary.
• Experience with git, CI/CD workflows, and containerization technologies (e.g., Docker, Kubernetes) is required.
• A strong understanding of software design principles and high-level code organization is essential.
• Desirable qualifications include experience with GPU and memory profiling techniques to optimize model performance.
• Familiarity with adjacent technologies such as hardware acceleration (GPUs), Linux, and C/C++ is a plus.
• The ability to design new model architectures tailored to specific problem domains is desirable.
• Familiarity with web technologies (e.g., HTTP, HTML, JavaScript) and their application in machine learning systems is beneficial.
• Experience applying machine learning to novel problems from conception to production is a plus.

Benefits:

• As a new Zytan, you will become part of a self-motivated, progressive, multi-cultural team.
• You will have the freedom and flexibility to work from where you do your best work.
• You will work with cutting-edge open-source technologies and tools.
• The position offers 35 days of paid holidays.