Lead Machine Learning Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇧🇬 Bulgaria – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 14%

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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RecruityTalent

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2024

💼 Consulting

📦 Logistics

🎯 Recruiter

Consulting • Logistics • Recruitment

RecruityTalent is a recruitment agency that partners with companies to manage the full hiring lifecycle, offering standard and flexible solutions through onsite recruitment projects and agency services. It provides end-to-end hiring support — including job postings, candidate sourcing, screening, interviews and offer management — with experience in IT, BPO and executive search, aligning hiring to clients' business vision and company culture.

📋 Description

• Deliver best-in-industry machine learning models for detecting subrogation opportunities using the latest ML advancements and software engineering practices • Meet and collaborate with business stakeholders, including customers, sales, and product managers, to drive development of new models and features • Collaborate with data engineering and software engineering teams to ensure smooth data flow across teams and APIs related to outbound subrogation • Mentor junior ML engineers in the outbound subrogation team to build a high-performing team

🎯 Requirements

• Deep understanding of the ML lifecycle: development, evaluation, deployment, monitoring, and iteration • Excellent communication skills and ability to explain complex technical concepts to non-technical stakeholders • Hands-on experience in experiment design and model evaluation • Expertise in ML system design, model deployment, and production ML systems • Experience engineering production-grade GenAI features with robust validation, sanity checks, and structured outputs to mitigate hallucination and business risk • Proficiency with AWS ML stack, including SageMaker, Lambda, Step Functions, and IAM • Strong software engineering fundamentals and best practices, including CI/CD, Test-Driven Development, and Infrastructure as Code • Experience translating business objectives into technical roadmaps and deliverables • Ability to balance technical excellence with business priorities and timelines • Strong stakeholder management and cross-functional collaboration skills • English level: Upper-Intermediate • Experience in subrogation, claims processing, insurance, or financial technology is nice to have

🏖️ Benefits

• Remote work arrangement • English level: Upper-Intermediate