Trase is an AI company co-founded in 2023, focused on simplifying AI deployment and management for enterprises.
The Senior Machine Learning Engineer will develop and refine machine learning systems, focusing on model training, pipeline development, and fine-tuning large language models (LLMs).
Responsibilities include architecting, building, and optimizing ML systems for real-world applications, designing training pipelines, and implementing feedback systems to improve ML models.
The role requires collaboration with product and business teams to translate requirements into effective ML solutions.
Staying current with ML advancements and mentoring junior team members are also key aspects of the position.
The engineer will communicate ML methodologies and insights to non-technical stakeholders.
Some travel is required for this position.
The salary range for this role is $175,000-$225,000, depending on experience and skills.
Requirements:
Proven experience in developing, optimizing, and deploying ML systems in production environments is essential.
A strong background in building and managing end-to-end training pipelines for ML models is required.
Extensive knowledge and hands-on experience in fine-tuning large language models for specific use cases is necessary.
Proficiency in ML frameworks such as TensorFlow, PyTorch, or similar tools is expected.
Candidates must be proficient in Python, focusing on writing efficient, clean, and maintainable code for ML applications.
The ability to communicate complex ML concepts clearly to both technical and non-technical audiences is crucial.
A Bachelor’s or Master’s degree in Machine Learning, Computer Science, Data Engineering, or a related field is required.
A track record of delivering impactful machine learning solutions that drive value in real-world applications is necessary.
Benefits:
The position offers a competitive salary along with performance-based bonuses.
A comprehensive health and wellness benefits package is provided.
Flexible work hours are available to accommodate work-life balance.
Opportunities for professional development and continued learning are encouraged.
The work environment is collaborative and inclusive, promoting teamwork and diversity.
