Mindbeam AI
1 - 10 employees
Founded 2024
🤖 Artificial Intelligence
🤝 B2B
Artificial Intelligence • B2B
Mindbeam AI is a company building Litespark, an ultra-fast LLM pretraining framework that accelerates training and inference for generative AI applications. Its software improves throughput on existing GPU hardware with zero code changes, is compatible with industry-standard ML frameworks like PyTorch, and claims to reduce pretraining time from months to days while lowering energy consumption and costs (up to ~81% energy savings in cited workloads). Mindbeam targets enterprise and B2B customers seeking scalable, efficient AI infrastructure for large language model development.
Machine Learning Engineer – Post Training
Job not on LinkedIn
🕒 May 20
🇺🇸 United States – Remote
💵 $150k - $190k / year
⏰ Full Time
🟢 Junior
🟡 Mid-level
🤖 Machine Learning Engineer
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Mindbeam AI
1 - 10 employees
Founded 2024
🤖 Artificial Intelligence
🤝 B2B
Artificial Intelligence • B2B
Mindbeam AI is a company building Litespark, an ultra-fast LLM pretraining framework that accelerates training and inference for generative AI applications. Its software improves throughput on existing GPU hardware with zero code changes, is compatible with industry-standard ML frameworks like PyTorch, and claims to reduce pretraining time from months to days while lowering energy consumption and costs (up to ~81% energy savings in cited workloads). Mindbeam targets enterprise and B2B customers seeking scalable, efficient AI infrastructure for large language model development.
📋 Description
• Develop pipelines for post-training tasks such as fine-tuning, evaluation, and model compression. • Implement scalable systems for model deployment, monitoring, and optimization. • Collaborate with researchers to validate experimental results in production contexts. • Build tools to automate benchmarking and regression testing. • Identify opportunities to improve efficiency in resource utilization and inference speed.
🎯 Requirements
• Bachelor’s, Master’s, or PhD in Computer Science, ML/AI, or related field—or equivalent practical experience. • 2+ years of experience in model training, evaluation, or deployment. • Strong skills in Python, ML frameworks (PyTorch/TensorFlow), and data pipeline tools. • Familiarity with optimization techniques (quantization, pruning, distillation). • Hands-on experience deploying models on cloud and/or GPU infrastructure. • Knowledge of monitoring and observability tools.
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