Machine Learning Engineering Coordinator

Job not on LinkedIn

🔥 21 hours ago

🇧🇷 Brazil – Remote

💵 R$23k - R$24k / month

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 11%

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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Combine | Global Recruitment

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

🎯 Recruiter

🤝 B2B

Recruitment • B2B

Combine | Global Recruitment is a Latin America-focused recruitment and staffing firm that helps companies build high-performing teams with pre-vetted LATAM professionals. They offer Outsourcing (handling vetting, compliance and payroll), Direct Hire (full talent acquisition and integration as direct employees), and Executive Search for C-suite and senior management roles. Their website emphasizes precision, compliance, and impact, and notes that over 200 companies use their Latin America recruitment solutions.

📋 Description

• Build the machine learning engineering layer for the function • Automate data pipelines and retraining routines • Implement model versioning and a model registry • Build continuous monitoring for models in production • Create and optimize machine learning algorithms • Model, tune, and continuously improve the performance of models in production • Deploy models to production and keep them healthy at a scale of hundreds of thousands of calls per day • Use production data to guide accuracy priorities • Directly lead a team of three people • Conduct one-on-ones, provide feedback, support career development, and manage prioritization • Bring industry best practices to ML engineering practices • Connect the team’s work to business outcomes and product teams • Remain hands-on and contribute code

🎯 Requirements

• Strong experience in traditional machine learning, with proprietary models running in production • Experience in modeling, tuning, and continuous improvement • Experience deploying models to production and maintaining them after deployment • Practical MLOps experience, including containerization, model versioning and registries, orchestration, and retraining pipelines • Proven experience leading people • Open, direct, and assertive communication • Python and its standard ecosystem • Preferred: applied computer vision, segmentation, classification, OCR, and fine-tuning vision foundation models • Preferred: experience in fraud prevention, KYC, biometrics, document analysis, or risk • Preferred: experience building an ML practice from the ground up • Preferred: experience working in lean environments • Preferred: ability to bridge technical teams and business functions

🏖️ Benefits

• Annual profit-sharing bonus equivalent to 2–3 monthly salaries • Health and dental insurance • Benefits card with meal and food allowances • Wellness and physical activity platform • Transportation allowance • Life insurance equivalent to 24 monthly salaries