Remote Artificial Intelligence Engineer – Work from Anywhere – Build the Future of AI

Join a globally distributed team that ships cutting‑edge machine‑learning products from day one. As a Remote Artificial Intelligence Engineer you will design, train, and deploy models that power real‑world applications for millions of users, all while enjoying the freedom to work from the location of your choice.

About the Role

We are looking for a passionate AI engineer who thrives on turning research into production‑grade systems. You will collaborate with product managers, data scientists, and software engineers to define model architectures, optimize training pipelines, and ensure scalable inference across cloud and edge environments. This position is 100 % remote—no office commute, no relocation required.

Key Responsibilities

• Design, implement, and maintain deep‑learning models for natural language processing, computer vision, and recommendation systems.
• Build reproducible training workflows using modern MLOps tooling (e.g., MLflow, Kubeflow, DVC).
• Optimize model latency and memory footprint for high‑throughput inference on GPUs, TPUs, and specialized accelerators.
• Conduct rigorous experimentation, A/B testing, and monitoring to validate model performance in production.
• Mentor junior engineers and contribute to internal best‑practice guides for responsible AI development.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related quantitative field (or equivalent experience).
• 3+ years of hands‑on experience building and deploying deep‑learning models in production.
• Proficiency in Python and major frameworks such as PyTorch, TensorFlow, or JAX.
• Strong grasp of distributed training, model quantization, and ONNX/TensorRT deployment.
• Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes).
• Excellent written and verbal communication skills for asynchronous, cross‑time‑zone collaboration.

Preferred Qualifications

• Publications at top-tier conferences (NeurIPS, ICML, CVPR, ACL) or a strong open‑source portfolio.
• Familiarity with large‑language‑model fine‑tuning, prompt engineering, and retrieval‑augmented generation.
• Background in data‑privacy techniques (federated learning, differential privacy).
• Experience building data‑centric tooling for annotation, versioning, and quality assurance.

Salary Range

$130,000 – $180,000 USD per year, commensurate with experience, expertise, and geographic cost‑of‑living adjustments.

Benefits & Perks

• Fully remote work with a generous home‑office stipend ($2,000 annually).
• Comprehensive health, dental, and vision coverage for you and dependents.
• Unlimited paid time off plus 10 company‑wide holidays.
• Annual learning budget ($3,500) for courses, conferences, and certifications.
• Equity grant and performance‑based bonuses.
• Quarterly virtual hackathons and AI research reading groups.

Our Culture

We operate on a trust‑first, outcomes‑driven philosophy. Teams set their own sprint cadence, communicate through transparent async channels, and gather for a weekly virtual “demo day” to celebrate shipped features. Diversity of thought is not a buzzword here—it’s the engine that fuels our model innovation.

How to Succeed in This Role

Success means delivering models that move key product metrics while maintaining rigorous standards for reproducibility, fairness, and security. You’ll thrive if you love iterating fast, documenting everything, and turning ambiguous research problems into reliable, scalable services that delight users worldwide.