AI Engineer

Job not on LinkedIn

🕒 September 21

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI 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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Jobberman Nigeria

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2009

🎯 Recruiter

👥 HR Tech

💰 Seed on 2010-02

Recruitment • HR Tech

Jobberman Nigeria is an online jobs marketplace and recruitment platform serving Nigeria. It connects job seekers and employers with listings across functions, locations, and experience levels, and provides employer services (job posting, verified employer accounts, executive recruitment, Pro Recruit and standard listings). The platform also offers career tools — including an AI Career Tool for CV and cover letter creation, mock interviews, salary negotiation assistance — plus skills assessments, learning resources, and job-matching features. Jobberman emphasizes accessibility (welcoming applications from persons with disabilities) and reports a large user base of job seekers and active hiring companies.

📋 Description

• Design, train, fine-tune, and assess machine learning and deep learning architectures for natural language processing, computer vision, predictive analytics, and classification applications • Develop and deploy large language model applications, including conversational agents, retrieval-augmented generation platforms, autonomous AI agents, and automated processes • Integrate third-party AI APIs and open-source model repositories into existing product frameworks • Manage the end-to-end data lifecycle for model training and real-time inference • Engineer robust model deployment pipelines using containerization and cloud infrastructure • Monitor deployed systems for performance, operational costs, and latency, and implement iterative improvements • Collaborate with product management, engineering, and design teams to identify high-impact AI opportunities • Maintain documentation of experimental methodologies, architectural decisions, and model performance outcomes

🎯 Requirements

• Experience designing, training, fine-tuning, and assessing machine learning and deep learning architectures • Knowledge of natural language processing, computer vision, predictive analytics, and classification tasks • Experience developing and deploying large language model applications, including conversational agents, retrieval-augmented generation (RAG) platforms, autonomous AI agents, and automated processes • Experience integrating third-party AI APIs and open-source model repositories into existing product frameworks • Experience managing data lifecycles, including collection, cleansing, labeling, and pipeline construction • Experience engineering model deployment pipelines using containerization and cloud infrastructure • Knowledge of API services, high availability, scalability, performance metrics, operational costs, and latency monitoring • Ability to collaborate with product management, engineering, and design teams • Ability to document experimental methodologies, architectural decisions, and model performance outcomes