🚀 Senior Machine Learning Engineer in Boston

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At Code Metal, we transform vast datasets, advanced AI models and high-performance infrastructure into actionable intelligence. As a Machine Learning Engineer, you will play a critical role in designing, training and deploying production‑grade AI systems that drive decision‑making at scale. This is a hands on position where technical excellence, experimentation and collaboration converge to deliver solutions with real world impact.

• Build robust, scalable pipelines for model training and inference, ensuring reliability and reproducibility.
• Implement, refine and extend core models and frameworks to achieve state of the art performance.
• Design, execute and analyze experiments to translate research insights into actionable AI solutions.
• Collect, clean and synthesize high quality data for training models, both in the wild and generated.
• Review the latest literature, implement new techniques, and integrate them into production‑ready systems.
• Provide technical leadership through code reviews, design discussions, and best practice guidance.

Why Code Metal?

• Impactful work: your models support decisions that shape complex systems and operations.
• High‑velocity environment: small, focused teams with rapid iteration cycles.
• Ownership and responsibility: every engineer contributes directly to production systems that matter.

Requirements

• Bachelor’s degree in Computer Science or a closely related field
• 2+ years experience training and deploying deep learning models
• 3+ years experience in full‑stack software engineering
• Proficient in Python and familiar with frameworks such as PyTorch and HuggingFace

Qualifications

• Advanced degree (MS/PhD) in Computer Science or related field
• Lead author publications at peer‑reviewed conferences such as NeurIPS, ICLR or ICML
• Experience with large scale LLM training in distributed computing environments

Benefits

• Health care plan with 100% premium coverage, including medical, dental and vision.
• 401k with 5% matching.
• Paid Time Off (Uncapped Vacation, plus Sick & Public Holidays).
• Flexible hybrid work arrangement.
• Relocation assistance for qualifying employees.

If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.