Senior Machine Learning Engineer

Job not on LinkedIn

🔥 15 minutes ago

🇧🇷 Brazil – Remote

💵 R$50k / month

⏳ Contract/Temporary

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 2%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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RHF Talentos

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2005

💼 Consulting

🏥 Healthcare

🎯 Recruiter

Consulting • Healthcare • Recruitment

RHF Talentos is a Brazilian human-resources franchisor and consultancy founded in 2005 that delivers recruitment, staffing, career services and HR solutions nationwide. With over 200 franchise units in 22 states and more than 15 million people impacted, the company offers recruitment and selection, temporary staffing, intern management, assessments, training, career coaching, and franchise opportunities. RHF emphasizes quality, operational reliability and social responsibility while serving companies (B2B) and jobseekers with HR programs such as employee mental-health initiatives and employer-focused diagnostics.

📋 Description

• Implement large-scale machine learning models from scratch. • Develop and implement custom CUDA kernels for model optimization. • Scale distributed training and inference pipelines on cloud infrastructure. • Architect and take hands-on ownership of machine learning systems with rigorous SLOs or production SLAs. • Deliver results quickly in ambiguous, fast-paced, early-stage environments. • Build internal tools or infrastructure to accelerate team productivity.

🎯 Requirements

• Built a large-scale foundational model from 0 to 1 at a high-growth AI/ML startup or a leading research lab. • Developed and implemented custom CUDA kernels for model optimization. • Hands-on experience scaling distributed training and inference pipelines on cloud infrastructure. • Experience architecting and taking hands-on ownership of machine learning systems with rigorous SLOs or production SLAs. • Demonstrated ability to deliver results quickly in ambiguous, fast-paced, early-stage environments. • Clear examples of tools or internal infrastructure built to accelerate team productivity. • Graduate-level education — specialization/MBA. • Skills: IT, systems engineering, risk analysis, data analysis.