ML Engineer: Scale AI Deployment & Optimization

Mindbeam; United States; On-site; USD 100,000 - 150,000; Full time

Job summary

Mindbeam is seeking a skilled professional to develop next-generation AI infrastructure. The role focuses on building pipelines for post-training tasks, implementing scalable deployment systems, and collaborating with researchers to ensure effective model validation.

Candidates should have strong Python skills, experience in model deployment, and a background in computer science or a related field. This role combines research and practical application, driving advancements in AI.

Qualifications

• Minimum 2 years of experience in model training, evaluation, or deployment.
• Hands-on experience deploying models on cloud and GPU infrastructure.
• Strong skills in Python and familiarity with ML frameworks.

Responsibilities

• Develop pipelines for post-training tasks such as fine-tuning and evaluation.
• Implement scalable systems for model deployment and optimization.
• Collaborate with researchers to validate experimental results.

Skills

Python

ML frameworks (PyTorch/TensorFlow)

Data pipeline tools

Optimization techniques

Monitoring and observability tools

Education

Bachelor’s, Master’s, or PhD in Computer Science, ML/AI, or related field

Job description

Mindbeam is seeking a skilled professional to develop next-generation AI infrastructure. The role focuses on building pipelines for post-training tasks, implementing scalable deployment systems, and collaborating with researchers to ensure effective model validation.

Candidates should have strong Python skills, experience in model deployment, and a background in computer science or a related field. This role combines research and practical application, driving advancements in AI.