Latest remote AI jobs
21 resultsMachine Learning Engineer
Train and ship large-scale models in production. Strong Python + PyTorch, distributed training experience.
AI Engineer — LLM Applications
Build LLM-powered products end to end — retrieval, evals, agents. Fully remote, top of market.
AI/ML Research Scientist
Publish and prototype frontier research. PhD or equivalent; deep learning, RL, or LLMs.
Senior Data Scientist
Own experimentation and ML-driven product decisions. SQL, Python, causal inference.
MLOps Engineer
Build the ML platform — training pipelines, serving, observability. K8s, Python, cloud.
Computer Vision Engineer
Perception models for autonomy. PyTorch, real-time inference, large image/video datasets.
NLP Engineer
Ship open-source NLP/LLM tooling used by millions. Transformers, tokenization, evals.
Data Engineer — ML Platform
Build the data foundations powering ML. Spark/SQL, streaming, reliability.
Applied AI Engineer (GenAI)
Turn frontier models into shipped features. Prompting, RAG, fine-tuning, latency tuning.
Machine Learning Engineer — Recommendations
Personalization models at massive scale. Strong ML fundamentals + production rigor.
Prompt Engineer
Design, test, and optimize prompts + eval suites for enterprise LLM deployments.
Senior Data Scientist — Experimentation
Drive product strategy with experimentation and ML. Stats depth, Python, communication.
Computer Vision Engineer
CV models + CUDA-accelerated pipelines. Deep learning, optimization, edge deployment.
Research Engineer — Foundation Models
Train and scale foundation models. Distributed training, PyTorch, research mindset.
MLOps / ML Platform Engineer
Scale model training + inference infra for the community. Python, K8s, GPUs.
DATA & ARTIFICIAL INTELLIGENCE ADVISOR
The USSTRATCOM Data and Artificial Intelligence Advisor serves as a Highly Qualified Expert (HQE) and principal advisor to the Commander and senior leadership. The role drives the strategic integration of Artificial Inte
Instructor/Assistant/Associate/Professor - STEM and Artificial Intelligence
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Senior AI Engineer
Are you a talented Senior AI Engineer looking for a remote job that lets you show your skills and get decent compensation? Look no further than Lemon.io — the marketplace that connects you with hand-picked startups in th
Senior Data Engineer
Are you a talented Senior Data Engineer looking for a remote job that lets you show your skills and get decent compensation? Look no further than Lemon.io — the marketplace that connects you with hand-picked startups in
Senior Independent AI Engineer / Architect
Senior Independent AI Engineer / Architect Remote | Americas, Europe, or Israel Most AI engineers can find work. Finding work worth doing is harder. A.Team is an invite-only network of senior AI engineers, ML engineers,
ML Engineer
At Trunk Tools, weâre the leading AI company revolutionizing construction, the second-largest industry on earth. We recently raised a $40M Series B led by Insight Partners, bringing our total funding to $70M from top-t
The AI, machine learning & data science job market
The field breaks into a handful of distinct roles. Machine learning engineers build and ship models in production and lean heavily on Python, PyTorch or TensorFlow, and distributed training. AI/LLM engineers work a layer up, turning foundation models into products with prompting, retrieval-augmented generation, fine-tuning, agents, and eval suites. Data scientists own experimentation, statistics, and ML-driven decisions (SQL, Python, causal inference, A/B testing). MLOps and ML platform engineers build the pipelines, serving, and observability that keep models running, usually on Kubernetes and a major cloud. Computer vision and NLP engineers specialize in perception and language, while research scientists (often with a PhD) prototype and publish new methods. Data engineers build the pipelines everything else depends on.
Hiring comes from several employer categories. Frontier labs like OpenAI, Anthropic, Google DeepMind, and Mistral pay the top of the market. Big tech and consumer-scale companies (Meta, Netflix, Tesla, NVIDIA, Airbnb) run large ML and personalization teams. AI infrastructure and data companies such as Databricks, Scale AI, Hugging Face, and Stripe hire across platform and applied roles. Beyond those, a growing wave of startups, enterprises adding AI to existing products, consultancies, and the U.S. federal government (via USAJobs) are all hiring. Much of this work is remote or remote-friendly, though San Francisco, New York, Seattle, and Austin remain dense hubs.
US pay is high and spread wide. Applied and mid-level roles commonly land in the $140k-$260k total-comp range; senior ML and data science roles at strong companies run roughly $250k-$400k; and research scientists or senior engineers at frontier labs and top tech firms can exceed $450k-$500k with equity. In-demand skills right now: solid Python, PyTorch, and the transformer/LLM stack (RAG, fine-tuning, evals, vector databases); classical ML and statistics for data science roles; and cloud, Kubernetes, and pipeline tooling (Spark, Airflow, MLflow) for platform and MLOps work. Depth in one area plus the ability to ship to production is what separates offers from rejections.
Frequently asked questions
How much do AI and machine learning jobs pay in the US?
It varies a lot by level and employer. Applied and mid-level roles typically fall in the $140k-$260k total-comp range, senior ML engineers and data scientists at strong companies run about $250k-$400k, and research scientists or senior engineers at frontier labs can top $450k-$500k with equity. Federal AI/ML roles pay on the government GS scale, which is lower in base but comes with stability and benefits.
Are these roles remote?
Many are. AI/ML has stayed more remote-friendly than most fields, and a large share of the listings here are remote (US) or remote (global). That said, some teams still want you in a hub like San Francisco, New York, Seattle, or Austin, so we tag location on every listing and let you filter by it.
What skills and background do I actually need?
For most engineering roles: strong Python, a deep-learning framework (usually PyTorch), and real production experience. LLM/GenAI roles want the modern stack (RAG, fine-tuning, evals, agents); data science roles want statistics, SQL, and experimentation; MLOps roles want cloud, Kubernetes, and pipeline tooling. A relevant degree helps, and research scientist roles often expect a PhD or equivalent publications, but shipped projects and a strong portfolio increasingly matter as much as credentials.
Do I need a certification to get hired in AI/ML?
Generally no. Employers in this field weigh demonstrated ability (projects, contributions, past production work) far more than certificates. Cloud certs (AWS, GCP) can help slightly for MLOps and platform roles, but no cert substitutes for being able to build and ship. Time is usually better spent on a solid portfolio than on collecting certifications.
How often are new jobs added, and where do they come from?
The board refreshes on a daily cycle. Listings are aggregated live from real employers' public feeds (Remotive and RemoteOK for remote roles, USAJobs for federal AI/ML positions), filtered strictly to genuine AI/ML titles. Older posts age off automatically, and every listing links to the employer's own application page. Nothing here is fabricated.