Remote Artificial Intelligence Engineer – US-Based Opportunity – Shape the Future of Generative AI

Join a pioneering AI research lab as a Remote Artificial Intelligence Engineer and architect scalable machine learning systems that power next-generation products. We offer a fully distributed culture, competitive compensation up to $220,000, and the autonomy to solve complex problems without bureaucracy.

About the Role

We are seeking a Senior Artificial Intelligence Engineer to join our core modeling team. In this role, you will design, train, and deploy large-scale foundation models and specialized neural architectures. You will collaborate closely with research scientists and platform engineers to transition cutting-edge prototypes into robust, production-grade services serving millions of users globally. This is a high-impact individual contributor role ideal for an engineer who thrives at the intersection of deep learning theory and large-scale distributed systems.

What You Will Own

• End-to-end lifecycle of deep learning models: data curation, architecture design, distributed training, evaluation, and optimized inference deployment.
• Optimizing training throughput on GPU clusters (thousands of GPUs) using frameworks like PyTorch, JAX, and Megatron-LM.
• Building and maintaining MLOps pipelines for continuous integration, automated testing, and reproducible model versioning.
• Researching and implementing novel techniques in quantization, distillation, and speculative decoding to reduce inference latency and cost.
• Mentoring junior engineers and establishing best practices for code quality, experiment tracking, and documentation.

Requirements

We value demonstrated capability over specific credentials. However, successful candidates typically exhibit the following profile:

Technical Expertise

• Deep Learning Mastery: 5+ years of hands-on experience designing and training neural networks (Transformers, Diffusion Models, LLMs).
• Distributed Systems: Proven track record scaling training across multi-node clusters (Slurm, Kubernetes, Ray) with expertise in FSDP, DeepSpeed, or Megatron.
• Programming Fluency: Expert-level Python; strong proficiency in C++ or Rust for high-performance kernel writing and inference optimization (TensorRT, vLLM, Triton).
• Data Engineering: Experience building petabyte-scale data processing pipelines (Spark, Polars, Ray Data) for pre-training and fine-tuning datasets.

Soft Skills & Mindset

• First-principles thinker capable of debugging non-deterministic training runs and silent data corruption.
• Excellent asynchronous communication skills; comfortable writing detailed RFCs and design docs for a global remote team.
• Passion for open-source contribution; active GitHub profile or publications in top-tier venues (NeurIPS, ICML, ICLR) are a significant plus.

Salary Range & Compensation Package

We believe in transparent, market-leading pay. Our compensation package is designed to attract the top 1% of talent regardless of geography.

Base Salary Estimation

$185,000 – $220,000 USD/year (Final offer determined by experience level, depth of systems expertise, and interview performance).

Total Rewards Breakdown

• Equity: Generous ISO grant (0.05% – 0.15% ownership) with a 4-year vesting schedule and 1-year cliff.
• Annual Bonus: Performance-based target of 15–20% of base salary.
• Compute Stipend: $5,000/year personal cloud compute budget (AWS, GCP, Lambda Labs, RunPod) for experimentation.
• Sign-On Bonus: $25,000 – $40,000 for exceptional candidates relocating from FAANG or top-tier labs.

Benefits & Remote-First Perks

Our benefits are built for the modern knowledge worker. Because we are 100% remote, we invest heavily in your home environment and well-being.

Health & Financial Security

• 100% employer-paid premiums for Medical, Dental, and Vision (Employee + Dependents).
• 401(k) with 6% employer match (immediate vesting).
• Comprehensive Life, AD&D, and Long-Term Disability insurance.
• HSA/FSA matching contributions up to $1,500 annually.

Work-Life Integration

• Unlimited PTO: Mandatory minimum 15 days off enforced per year; company-wide “Recharge Weeks” twice annually (July & December).
• Home Office Budget: $3,000 one-time setup stipend + $1,200/year refresh allowance (monitors, ergonomic chairs, GPUs).
• Co-working Access: Global WeWork/Industrious membership or local stipend up to $300/month.
• Learning & Development: $3,000/year budget for conferences (NeurIPS, KubeCon), courses, certifications, and books.

Culture & Connection

• Quarterly all-expenses-paid team offsites (previous locations: Lisbon, Tokyo, Austin, Banff).
• Monthly “Deep Work” days: No meetings allowed, calendar blocked for flow state.
• Parental Leave: 20 weeks fully paid for primary caregivers; 8 weeks for secondary.
• Mental Health: Free access to Modern Health / Headspace; therapy stipend included.

Our Tech Stack

We pick the right tool for the job, but our core stack is modern and opinionated:

• Modeling: PyTorch, JAX/Flax, Hugging Face Transformers/Accelerate/PEFT
• Infrastructure: Kubernetes (EKS/GKE), Terraform, Argo Workflows, Ray Cluster
• Data: Apache Iceberg, Spark, Dagster, Weights & Biases / MLflow
• Inference: vLLM, TensorRT-LLM, Triton Inference Server, BentoML
• Observability: Datadog, Prometheus/Grafana, Arize/Phoenix for LLM eval

Hiring Process & Timeline

We respect your time. Our process is rigorous but efficient, typically completing in 3 weeks.

1. Recruiter Screen (30 min): Alignment on values, career trajectory, and logistics.
2. Technical Deep Dive (60 min): Live coding session focused on PyTorch internals, CUDA kernels, or distributed training debug scenarios.
3. System Design (90 min): Design an end-to-end MLOps platform or a scalable inference architecture for a 70B parameter model.
4. Research & Culture Panel (60 min): Discussion with Research Scientists and Peers on recent papers, open-source philosophy, and collaboration style.
5. Offer & Onboarding: Reference checks followed by a detailed offer package. Start dates are flexible.

Why Join Us Now?

We are at an inflection point. With a recent Series C funding round led by top-tier VCs (Sequoia / a16z / Benchmark), we have the runway to pursue AGI-level ambition without the pressure of short-term monetization. You will have immediate access to one of the largest private GPU clusters in the world (10k+ H100s) and a dataset portfolio that is the envy of the industry. If you want your code to define the next paradigm shift in computing—rather than optimizing ad click-through rates—this is your home.