AI Research Engineer

Location: 100% remote within the United States

Salary: $100,000–$150,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Design, prototype, and evaluate applied AI solutions for natural language, computer vision, recommendation, and structured data use cases.
• Translate business problems into ML formulations with measurable success criteria and rigorous evaluation strategies.
• Research deep learning, large language models, and related techniques, assessing their applicability to internal products and services.
• Build production-quality training and inference pipelines, including dataset construction, labeling, validation, monitoring, and observability.
• Optimize models and infrastructure for accuracy, latency, throughput, cost, and efficient use of compute and accelerator resources.
• Collaborate with product, design, domain, and platform teams while mentoring engineers and influencing the AI roadmap.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent applied experience.
• At least six years of combined research and applied ML engineering experience; the position lists 10+ years of experience required.
• Strong proficiency in Python and modern ML frameworks such as PyTorch or JAX.
• Hands-on experience training, fine-tuning, and evaluating deep learning models at non-trivial scale.
• Experience moving ML models from research prototypes to production, with observability, safeguards, distributed training, mixed precision, and accelerator hardware.
• Applicants must be based in the United States and must be U.S. citizens, Green Card holders, EAD holders, or eligible for an H-1B transfer.

Nice to have

• Published research at leading AI/ML venues.
• Experience with large language model training, fine-tuning, or evaluation.
• Familiarity with retrieval-augmented generation, agentic systems, multimodal architectures, responsible AI, model alignment, or open-source ML projects.

Culture & Benefits

• Full-time direct W-2 employment.
• Opportunity to work across applied research and production engineering.
• Collaboration with ML platform, product, design, and domain experts.
• Work focused on safety, fairness, reliability, and responsible deployment of AI systems.