Artificial Intelligence Engineer

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About UltraSafeAI

UltraSafeAI is a US-based technology company at the forefront of developing secure, reliable, and explainable AI systems. We specialize in proprietary AI technologies including advanced LLMs, CNNs, VLLMs, intelligent agents, computer vision systems, and cutting-edge ML algorithms. Our focus is on B2B AI adoption, providing end-to-end integration using our proprietary technology stack to automate entire business processes.

We create intelligent solutions that prioritize safety, transparency, and human alignment across various industries including healthcare, finance, legal, and enterprise services. Our mission is to enable seamless AI adoption while maintaining the highest standards of safety and ethical considerations.

Position Overview

We're seeking an experienced AI Research Engineer specializing in model training, fine-tuning, and optimization of large language models (LLMs), vision language models (VLMs), and convolutional neural networks (CNNs). The ideal candidate will have deep expertise in training and fine-tuning foundation models using advanced techniques and frameworks, with particular emphasis on reinforcement learning approaches for alignment.

As an AI Research Engineer at UltraSafeAI, you'll work on developing and enhancing our proprietary models, creating domain-specific adaptations, and optimizing inference performance. You'll collaborate with our engineering team to build the core AI capabilities that power our enterprise solutions and set new standards for AI performance and safety in business applications.

Key Responsibilities

● Train and fine-tune large language models (LLMs) and vision language models (VLMs) using state-of-the-art techniques

● Implement and improve reinforcement learning methods for model alignment, including DPO, PPO, and GRPO

● Develop and optimize CNNs for specialized computer vision tasks in enterprise contexts

● Work with distributed training frameworks for efficient model development

● Optimize models for inference using libraries like VLLM, SGLANG, and Triton Inference Server

● Implement techniques for reducing model size while maintaining performance (quantization, distillation, pruning)

● Create domain-specific adaptations of foundation models for vertical industry applications

● Design and execute experiments to evaluate model performance and alignment

● Develop benchmarks and metrics to measure improvements in model capabilities

● Collaborate with data science team on dataset curation and preparation for training

● Document model architectures, training procedures, and experimental results

● Stay current with the latest research in model training and alignment techniques

Required Qualifications

● 4-5+ years of professional experience in AI/ML engineering with focus on model training

● Strong expertise in training and fine-tuning large language models

● Experience with major deep learning frameworks (PyTorch, TensorFlow, JAX)

● Hands-on experience with model training libraries and frameworks (Transformers, NeMo, Megatron-LM, TRL)

● Practical implementation of reinforcement learning techniques for model alignment (DPO, PPO, GRPO)

● Experience optimizing models for efficient inference

● Strong understanding of distributed training techniques for large models

● Background in computer vision model development (CNNs, vision transformers)

● Excellent programming skills in Python and related data science tools

● Experience with cloud infrastructure for ML workloads (AWS, GCP, or Azure)

● Strong problem-solving skills and scientific mindset

● Excellent documentation and communication abilities

Highly Desirable

● Experience with multimodal models combining text, vision, and other modalities

● Knowledge of model quantization techniques (QLoRA, GPTQ, AWQ)

● Experience with VLLM, SGLANG, or Triton Inference Server for optimized inference

● Background in prompt engineering and instruction tuning

● Familiarity with RLHF (Reinforcement Learning from Human Feedback)

● Experience with model evaluation and red-teaming

● Knowledge of AI safety and alignment research

● Experience with domain-specific model adaptation for industries like healthcare, finance, or legal

● Background in research with publications or contributions to open-source ML projects

● Experience with MLOps tools and practices for model lifecycle management

Why Join UltraSafeAI?

● Create Proprietary AI Models: Develop the core AI technologies that power our enterprise solutions

● 100% Remote Work: Work remotely with our US-based company with flexible hours

● B2B Impact: Help shape AI models that solve real business problems across industries

● Cutting-Edge Research: Work on the frontier of AI model development and alignment

● Continuous Learning: Regular knowledge sharing sessions and education stipend

● Collaborative Team: Work with talented researchers and engineers focused on innovation

● Work-Life Balance: Flexible PTO policy and respect for personal time

● Career Growth: Clear paths for advancement in a rapidly growing company

● Industry-Leading Infrastructure: Access to high-performance computing resources for model training