Machine Learning Technologist
hace 3 días
Tbo is seeking a highly skilled Machine Learning Technologist to join our team and contribute to the development of innovative machine learning solutions. As a key member of our engineering team, you will be responsible for designing, implementing, and deploying machine learning models and algorithms to drive business growth and improve customer experiences.
Key Responsibilities:
- Design and develop machine learning models and algorithms for various aspects of the localization and business workflow processes, including machine translation, LLM fine-tuning, and quality assurance.
- Take ownership of key projects from definition to deployment, ensuring that they meet technical requirements and maintain momentum and direction until delivery.
- Evaluate and select appropriate machine learning techniques and algorithms to solve specific problems.
- Implement and optimize machine learning models and technologies using Python, TensorFlow, and other relevant tools and frameworks.
- Perform statistical analysis and fine-tuning using test results.
- Deploy machine learning models and algorithms using appropriate techniques and technologies, such as containerization using Docker and deployment to cloud infrastructure.
- Use AWS technologies (including but not limited to Sagemaker, EC2, S3) to deploy and monitor production environments.
- Keep abreast of developments in the field, with a dedication to learning in the role.
- Document diligently and communicate thoughtfully about ML experimentation, design, and deployment.
- Project scope: Define and design solutions to machine learning problems. Integration with larger systems done with guidance from more senior colleagues.
Requirements:
- Effective model development: success is evident when the models developed are accurate, efficient, and align with project requirements.
- Positive team collaboration: demonstrated ability to collaborate effectively with various teams and stakeholders, contributing positively to project outcomes.
- Continuous learning and improvement: a commitment to continuous learning and applying new techniques to improve existing models and processes.
- Clear communication: ability to articulate findings, challenges, and insights to a range of stakeholders, ensuring understanding and appropriateness.
Skills and Knowledge:
- Ability to write robust, production-grade code in Python.
- Excellent communication and documentation skills.
- Strong knowledge of machine learning techniques and algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- Hands-on, high proficiency experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Experience with natural language processing (NLP) techniques and tools.
- Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience taking ownership of projects from conception to deployment, and mentoring more junior team members.
- Hands-on experience with AWS technologies including EC2, S3, and other deployment strategies. Experience with SNS, Sagemaker a plus.
- Experience with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, GPU deployments, etc.
Education and Experience:
- BSc in computer science, mathematics or similar field.
- Master's Degree is a plus.
- 3+ years' experience as a Machine Learning Engineer or similar role.
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