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 – Kernels
Job not on LinkedIn
🕒 May 21
🏄 California – Remote
💵 $150k - $190k / year
⏰ Full Time
🟢 Junior
🟡 Mid-level
🤖 Machine Learning Engineer
📊 Check your resume score for this job
Improve your chances of getting an interview by checking your resume score before you apply.
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
• Design and implement custom GPU/accelerator kernels to maximize performance. • Profile, benchmark, and optimize critical ML workloads. • Collaborate with researchers to translate algorithmic advances into efficient, production-ready code. • Stay current with hardware advancements (CUDA, ROCm, TPU) to inform kernel design. • Document and share best practices for low-level optimization.
🎯 Requirements
• Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or related field—or equivalent experience. • 2+ years of experience in GPU programming, parallel computing, or systems-level optimization. • Strong coding skills in C++, CUDA, or similar languages. • Familiarity with ML frameworks and their low-level backends. • Experience optimizing workloads for distributed and heterogeneous compute environments. • Comfort with profiling tools and performance diagnostics.
Apply NowSimilar Jobs
🕒 May 20
Guidehouse
10,000+ employees
MLOps Engineer responsible for designing and implementing platforms for the deployment of machine learning solutions. Collaborating with data scientists and engineers to operationalize models in federal environments.
🇺🇸 United States – Remote
💵 113k - 188k / year
💰 Grant on 2023-02
⏰ Full Time
🟡 Mid-level
🟠 Senior
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
🕒 May 20
Senior Full-Stack Developer leading the technical realization of generative AI roadmap for asset management solutions. Building tools that enhance expert judgment through sophisticated Agentic workflows.
🕒 May 20
AI/ML Engineer leading technical implementation of generative AI systems for enterprise, designing multi-agent systems and overseeing AI workflows, ensuring AI implementations are scalable and secure.
🕒 May 17
Machine Learning Engineer optimizing onboarding and re-entry experiences within Paramount's streaming services. Focusing on user commitment and personalization through advanced machine learning techniques.
🇺🇸 United States – Remote
💵 $124k - $186k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
🕒 May 15
Machine Learning Engineer advancing forecasting and predictive modeling in clean energy software platform. Owning the full lifecycle of ML model development with strong product influence.
🇺🇸 United States – Remote
💵 $180k - $230k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
🤖 Machine Learning Engineer
