AI/ML Engineer (LLMs & Applied AI)

TL;DR

AI/ML Engineer (LLMs & Applied AI): Transforming raw domain data into high-performance LLMs for intelligent applications with an accent on data preparation, fine-tuning, and validation of large language models. Focus on designing evaluation pipelines, integrating fine-tuned LLMs into production systems, and translating business requirements into applied AI solutions.

Location: Remote (Global)

Company

hirify.global develops Data Fusion and AI products, including Intellectus, a cloud-based all-in-one fusion platform, to combat crime and terror.

What you will do

• Curate, preprocess, and manage datasets for LLM and classical models training and evaluation.
• Fine-tune LLMs using techniques such as LoRA, QLoRA, or RLHF.
• Design evaluation pipelines and metrics to ensure model accuracy, robustness, and alignment with product goals.
• Integrate fine-tuned LLMs into production systems, supporting iterative improvements.
• Collaborate with cross-functional teams to translate domain knowledge and business requirements into applied AI solutions.

Requirements

• Strong Python programming, agile engineering mindset and data engineering skills.
• Hands-on experience with LLM frameworks (Hugging Face, PyTorch, TensorFlow).
• Expertise in dataset curation, preprocessing, and annotation for ML/AI tasks.
• Proven experience fine-tuning and validating LLMs.
• Knowledge of prompt engineering, model evaluation, and deployment best practices.

Nice to have

• Familiarity with AI agent frameworks or retrieval-augmented generation (RAG).
• Experience with reinforcement learning for language models (RLHF).
• Exposure to cloud-based ML pipelines (AWS, GCP, Azure).
• Background in classical ML (vision, time-series, tabular).
• Familiarity with MLOps tools.

Culture & Benefits

• Work from home with flexible hours.
• Receive a yearly performance bonus.
• Paid medical insurance and daily lunch allowance.
• Sport/Gym allowance and an Udemy unlimited subscription for learning and development.
• Comprehensive onboarding plan and equipment support.
• No dress code, with gifts and rewards for milestones.
• Participate in happy hours, coffee time, online team building, and company events.