AI Research Engineer

Location: 100% remote within the United States

Salary: $100,000–$150,000 annually

Company

Technology consulting and software development services covering 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 ambiguous business problems into measurable machine learning formulations, success metrics, and evaluation strategies.
• Research and assess modern deep learning and large language model techniques for practical internal applications.
• Build production-quality training and inference pipelines, including dataset construction, labeling, validation, monitoring, and observability.
• Optimize models and infrastructure for accuracy, latency, throughput, compute efficiency, and cost while collaborating with ML platform engineers.
• Implement safety, fairness, and reliability evaluations, document findings, mentor engineers, and influence the AI roadmap.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent applied experience.
• Six or more years of combined research and applied machine learning engineering experience.
• 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 and safeguards, including distributed and mixed-precision training.
• Applicants must be U.S. citizens, Green Card holders, EAD holders, or H-1B transfer candidates; new H-1B visa petitions cannot be sponsored.

Nice to have

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

Culture & Benefits

• Full-time direct W-2 employment.
• Career growth opportunities within an established organization.
• Work on high-impact business problems spanning applied research and production engineering.
• Contribute to internal knowledge sharing, reading groups, and prototype-to-production playbooks.