Remote Artificial Intelligence Engineer – United States – Build the Future of Intelligent Systems

Join a forward‑thinking team that ships production‑grade AI solutions from anywhere in the U.S. We’re looking for a passionate engineer who thrives on turning research into scalable products and loves the freedom of a fully remote workplace.

About the Role

As an Artificial Intelligence Engineer you will design, develop, and deploy machine‑learning models that power our core products. You’ll collaborate with data scientists, software engineers, and product managers to translate business problems into robust, maintainable AI pipelines. This position is 100 % remote, offering flexibility to work from any U.S. location while contributing to high‑impact projects that reach millions of users.

Key Responsibilities

• Architect end‑to‑end ML workflows – data ingestion, feature engineering, model training, validation, and serving.
• Implement state‑of‑the‑art algorithms (transformers, graph neural nets, reinforcement learning) using PyTorch, TensorFlow, or JAX.
• Optimize models for latency, throughput, and cost on cloud platforms (AWS, GCP, Azure) and on‑premise GPU clusters.
• Build reproducible CI/CD pipelines for model versioning, automated testing, and continuous deployment.
• Partner with product teams to define success metrics, run A/B experiments, and iterate quickly.
• Mentor junior engineers and contribute to internal best‑practice guides for responsible AI.

Requirements

Technical Expertise

• 3+ years of professional experience building production ML systems.
• Deep proficiency in Python and at least one major deep‑learning framework.
• Strong grasp of software engineering fundamentals: Git, Docker, Kubernetes, unit/integration testing.
• Experience with distributed training (Horovod, DeepSpeed, Ray) and model serving (TorchServe, Triton, TensorFlow Serving).

Data & MLOps

• Hands‑on with feature stores, data lakes, and orchestration tools (Airflow, Prefect, Dagster).
• Familiarity with model monitoring, drift detection, and automated retraining loops.

Soft Skills

• Excellent written and verbal communication – you’ll document design decisions and present results to non‑technical stakeholders.
• Self‑directed, comfortable working asynchronously across time zones.
• Commitment to ethical AI: bias mitigation, privacy, and transparency.

Preferred Qualifications

• Publications or open‑source contributions in top ML venues (NeurIPS, ICML, CVPR, etc.).
• Experience with large‑scale language models or multimodal architectures.
• Background in a regulated domain (healthcare, finance, autonomous vehicles) where compliance matters.

Benefits & Perks

• Fully remote – set up your ideal home office with a $2,000 annual stipend.
• Comprehensive health, dental, and vision coverage for you and dependents.
• Unlimited PTO plus 10 paid company holidays.
• 401(k) match up to 5 % and equity grant refreshed annually.
• Learning budget of $3,000/year for courses, conferences, and certifications.
• Quarterly virtual hackathons and an annual all‑hands retreat (travel covered).

Salary Range

Estimated compensation: $150,000 – $210,000 USD per year, plus equity and performance bonuses. Exact offer depends on experience, location‑based cost‑of‑living adjustments, and interview outcomes.

Company Culture

We operate as a distributed-first organization where trust, transparency, and continuous learning drive every decision. Our engineering culture emphasizes blameless postmortems, peer code reviews, and a shared ownership mindset. Diversity of thought is not a buzzword here – it’s a measurable advantage that shapes the AI systems we ship.

How to Succeed in This Role

• Stay curious: allocate time each week to read the latest papers and experiment with emerging techniques.
• Communicate proactively: share progress, blockers, and trade‑offs in our async channels (Slack, Notion, GitHub).
• Think product‑first: align model improvements with measurable user outcomes.
• Champion responsible AI: embed fairness checks and privacy safeguards into every pipeline.