{"id":3560068,"url":"https://alion.io/job/vaimo-ai-engineer","title":"AI Engineer","company":{"id":56554,"name":"Vaimo","domain":"vaimo.com","url":"https://alion.io/company/vaimo","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":70,"open_postings":20,"ghost_share":0.5,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-07T05:47:08Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pretoria, South Africa"],"countries":["ZA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"Linux","optional":false},{"name":"PHP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Transformers","optional":false},{"name":"FAISS","optional":true},{"name":"MLFlow","optional":true},{"name":"n8n","optional":true},{"name":"Ollama","optional":true},{"name":"Pinecone","optional":true},{"name":"RAG","optional":true},{"name":"Ray","optional":true},{"name":"Weaviate","optional":true},{"name":"Weights & Biases","optional":true}],"status":"live","first_seen_at":"2025-08-11T06:47:27Z","employer_posted_date":"2026-06-01","last_verified_at":"2026-11-06T16:58:08Z","board_verified":true,"closed_at":null,"days_open":453,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":452},"description":"About the Role\nWe’re looking for a skilled AI Engineer to help us fine-tune, deploy, and maintain private AI models tailored to our business needs. You’ll be working with leading foundation models and custom datasets to deliver scalable, secure, and high-performing AI solutions-without reinventing the wheel.\nWhat You’ll Do\nModel Fine-Tuning & Adaptation\nFine-tune pre-trained private AI models (e.g. LLMs, vision models) for specific business use cases.\nHost and manage local LLMs and app hosting\nWork with proprietary or internal datasets to adapt models for high relevance and accuracy.\nEvaluate model performance and improve outputs through prompt engineering or targeted retraining.\nData Preparation\nCollect, clean, and prepare datasets for training, tuning, and evaluation.\nCollaborate with data teams to ensure high-quality inputs and labeling consistency.\nDeployment & Operations\nDeploy models in secure, scalable production environments using Docker, Kubernetes, Linux and cloud infrastructure (AWS, GCP, or Azure).\nMonitor model performance, reliability, and drift; implement updates and improvements as needed.\nMaintenance & Optimisation\nMaintain and update deployed models to ensure continued alignment with business goals.\nOptimize model latency, cost, and accuracy based on real-world usage data.\nCollaboration & Support\nWork with product and engineering teams to integrate models into applications.\nSupport internal teams with prompt design, model usage, and troubleshooting.\nResponsible AI Practices\nApply principles of ethical AI development, including privacy, security, and bias mitigation.\nEnsure compliance with internal and external AI governance policies.\nWhat You’ll Need\n1+ years’ experience in AI/ML/GI engineering, with a focus on model fine-tuning and deployment.\nStrong experience with PHP, Node, React & Python and libraries like Transformers, LangChain, or Hugging Face.\nFamiliarity with model evaluation techniques and metrics.\nExperience deploying AI models in production using tools like Docker, Kubernetes, and cloud services (AWS, GCP, or Azure).\nSolid understanding of LLMs or other foundation models and how to work with them effectively.\nStrong analytical, problem-solving, and communication skills.\nNice to Have\nExperience with vector databases (e.g. FAISS, Weaviate, Pinecone) or RAG pipelines.\nKnowledge of secure and private model hosting (eg Ollama).\nCertifications in ML, cloud, or AI-related fields.\nExposure to tools like MLflow, Weights & Biases, or Ray.\nOrchestration automation like n8n\nWhy Join Us?\nYou’ll work on impactful AI solutions without the burden of building from scratch-just smart adaptation, deployment, and ongoing improvement. 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