Member of Technical Staff, Machine Learning

Job not on LinkedIn

🔥 0 minutes ago

🇪🇸 Spain – Remote

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.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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DNA325

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🎯 Recruiter

🤝 B2B

Recruitment • B2B

DNA325 is an IT recruitment agency that helps US and European companies hire technical and product talent quickly. Founded by digital-product professionals and active since 2016, the firm specializes in full-cycle IT recruitment for roles across software development, AI/ML, DevOps, QA, product and leadership, as well as marketing and operations functions supporting tech teams. DNA325 emphasizes fast sourcing (claims like 350+ professionals presented monthly and first candidates in 3 business days), thorough vetting including technical interviews and recorded English assessments, and recruitment coordination (interview scheduling, negotiations, onboarding support). It serves startups through larger businesses across industries such as SaaS, fintech, gaming, and digital product development, and offers market research, salary benchmarks, and ATS integration.

📋 Description

• Build and improve ML components across data, training, evaluation, and inference • Fine-tune and adapt models as part of larger production systems • Implement evaluation and testing to understand model behavior • Help build and maintain data pipelines for real-world and synthetic data • Debug model issues, performance problems, and production incidents • Ship improvements iteratively and learn from real user feedback • Work closely with senior ML engineers and product teams • Work under production constraints including latency, cost, reliability, and safety • Ensure ML models meet accuracy, latency, and reliability targets • Find, debug, and root-cause production issues • Maintain robust, reproducible, and maintainable data pipelines, training loops, and inference systems • Collaborate with engineering, product, and research teams to ship reliable ML-powered features

🎯 Requirements

• Strong foundations in machine learning and modern neural architectures • Some hands-on experience training, fine-tuning, or deploying ML models • Comfortable writing production-quality code and learning new tools quickly • Curious, coachable, and eager to learn from real production systems • Able to work through ambiguity with guidance, growing ownership over time • A bias toward shipping, iteration, and continuous improvement • Python • PyTorch / JAX • Experience with production ML systems running on GPUs

🏖️ Benefits

• Base salary and equity package, with compensation varying by location • Remote-first work environment

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