Staff ML Engineer for AI Generation Engine — Remote

SandboxAQ; United States; Remote; USD 173,000 - 286,000; Full time

Benefits offered by this job

Comprehensive medical, dental, and vision coverage

Retirement savings with company matching

Flexible paid time off

Career development opportunities

Job summary

A high-growth AI solutions company is seeking a Machine Learning Engineer to own the end-to-end ML lifecycle, developing AI-first products using Large Quantitative Models. The role involves designing robust data pipelines, implementing ML models, and collaborating with teams to translate business goals into ML solutions. Ideal candidates will have significant experience in software development, a strong Python background, and a proven track record in the ML lifecycle. This remote role offers competitive compensation ranging from $173,000 to $286,000 based on experience.

Qualifications

• 8+ years of experience in software development.
• Experience with scalable ML systems and large-scale data processing.
• Proven expertise in the full ML lifecycle.

Responsibilities

• Design and manage data pipelines for LQMs and agentic frameworks.
• Develop, test, and implement ML models and algorithms.
• Collaborate with cross-functional teams to achieve business goals.

Skills

Python

Machine Learning (PyTorch, TensorFlow)

Data Engineering

MLOps

Education

BS in Software Engineering or Computer Science

MS or PhD (highly desired)

Tools

GCP

AWS

Job description

A high-growth AI solutions company is seeking a Machine Learning Engineer to own the end-to-end ML lifecycle, developing AI-first products using Large Quantitative Models. The role involves designing robust data pipelines, implementing ML models, and collaborating with teams to translate business goals into ML solutions. Ideal candidates will have significant experience in software development, a strong Python background, and a proven track record in the ML lifecycle. This remote role offers competitive compensation ranging from $173,000 to $286,000 based on experience.