26,486 Verified AI Jobs (June 2026) - Verified Daily
Explore AI jobs across roles tied to machine learning, applied research, data science, product development, engineering, operations, and AI-focused support. Listings may include remote, hybrid, and on-site opportunities, with responsibilities ranging from model work and analytics to building AI-enabled products and workflows. Create an account to explore the full job feed and auto-apply with LiftmyCV AI Agent.
Machine Learning Engineer/AI Engineer
On-siteSertis, a leading Data and AI engineering firm located in Bangkok, is seeking a Machine Learning Engineer to enhance their AI solutions. The role involves productionizing advanced data science research, optimizing models, and building robust MLOps infrastructure. Ideal candidates will have at least three years of experience in AI/ML engineering, strong programming skills, and familiarity with generative AI concepts. You'll work in a collaborative environment and contribute to real-world applications across industries, ensuring innovative solutions for clients.
Posted 2 days ago
AI/Machine Learning Engineer
RemoteOddball is seeking an AI/ML Engineer to join their remote team, focusing on intelligent automation for a federal financial regulatory agency. The role involves designing, developing, and deploying AI/ML models, building ML pipelines in AWS, and collaborating with teams to improve workflows. Ideal candidates will have production experience with machine learning models, proficiency in Python, and the ability to work in agile environments. The position also requires US work authorization and may involve federal background checks.
Posted 1 week ago
.png?1776136408){kind=logo}
Machine Learning Engineer, AI
HybridBiohub is a revolutionary initiative focused on harnessing cutting-edge AI models and computational power to accelerate scientific discovery, particularly in the field of biology. As part of a unique team, you'll work on frontier AI for fundamental science, solving impactful problems that contribute to curing diseases. You'll handle diverse scientific data formats and develop infrastructure solutions that empower scientists globally. With a focus on collaboration, innovation, and best practices in MLOps, this role offers a remarkable opportunity to shape the future of AI in science.
Posted 4 weeks ago
AI/ML Engineer / Data Scientist
On-siteThe AI/ML Engineer/Data Scientist supports AI/ML-enabled analytics and related initiatives across the BMx FoS. This role focuses on developing use cases aligned with Government priorities while ensuring compliance with all governance requirements. The position collaborates with multiple stakeholders to analyze operational trends and support various analytical functions, such as predictive maintenance and anomaly detection, maintaining a focus on operational safety and cybersecurity.
Posted 2 days ago
Data Scientist (AI/ML Engineer)
HybridIFS is a leading global enterprise software company dedicated to providing innovative AI-driven solutions that enhance financial operations. The recruitment is for a Data Scientist (AI/ML Engineer) to design and implement machine learning models that optimize finance processes. The role involves collaborating with cross-functional teams to ensure seamless data integration and predictive analytics. IFS promotes a diverse and inclusive work environment, offering flexibility and a commitment to sustainability, inviting applicants who wish to make a substantial impact in their roles.
Posted 3 weeks ago
AI & ML Engineer
RemoteSandstone seeks an AI & ML Engineer to build AI-native operating systems for in-house legal teams. The role involves creating production AI systems, enhancing document understanding, and translating legal judgment into product behavior. As part of an elite team, you will collaborate across disciplines to deliver useful and trustworthy AI solutions in the legal domain. Experience in building applied AI products and strong software engineering fundamentals are essential. This position offers competitive benefits in a dynamic and collaborative environment.
Posted 1 day ago
AI/ML Engineer
On-siteGRVTY seeks an experienced AI/ML Engineer to join its data engineering team in McLean, VA. The role involves implementing RAG pipelines, integrating LLMs into applications, and developing REST API interactions. Candidates must have an active TS/SCI + Poly clearance and a strong background in AI/ML methodologies. The work environment is fast-paced and collaborative, focusing on innovation and flexibility. GRVTY offers comprehensive benefits and a supportive culture that values the well-being of its employees.
Posted 2 days ago
AI/ML Engineer
On-siteClera, an innovative AI startup, seeks an AI/ML Engineer to transform computer-aided engineering (CAE) through advanced AI technologies. In this role, you'll design, train, and deploy machine learning models to enhance simulation processes and engineering design automation. Collaborating with experts in AI and mechanical engineering, you will influence the future of engineering by improving simulation accuracy and efficiency. This position offers a unique opportunity to make a significant impact at an early-stage company, contributing to cutting-edge AI applications in engineering.
Posted 3 days ago
AI/ML Engineer
HybridRaft is seeking an AI/ML Engineer to work in Rome, NY, focused on building and deploying AI-powered solutions for military and government clients. The role involves developing machine learning models and integrating them into the company's AI platform, [R]AIMS. Candidates should have 3-6 years of experience, strong Python skills, and familiarity with modern ML frameworks. This hybrid position requires a U.S. citizenship and offers a competitive salary, with additional benefits including healthcare and PTO.
Posted 4 days ago
AI/ML Engineer
On-siteEllo is seeking an AI/ML Engineer to enhance education through innovative AI solutions. The engineer will collaborate with a skilled team to create tools that assist children in learning. Responsibilities include developing AI systems that personalize learning, working closely with education experts, and implementing effective evaluation metrics. Candidates should have significant experience in building AI products, strong programming skills, and a passion for improving child development. The role is based in San Francisco with a vibrant team focused on making a meaningful impact in education.
Posted 1 week ago
AI/ML Engineer
On-siteAvanceon seeks a passionate AI/ML Engineer to develop intelligent systems using semantic search, Retrieval-Augmented Generation (RAG), and multi-agent workflows. This role allows for involvement in cutting-edge AI solutions in NLP/NLU and applied AI, offering a chance to make a significant business impact and influence the future of automation. Key responsibilities include building semantic search pipelines and optimizing models, requiring strong Python and ML framework skills. A degree in Computer Science or a related field and a minimum of 1 year experience are essential. Avanceon promotes a collaborative and innovative culture with continuous learning opportunities.
Posted 2 weeks ago
AI/ML Engineer
RemoteRackner is seeking an AI/ML Engineer to design, develop, and deploy advanced machine learning solutions for mission-critical systems. This role focuses on building scalable models and collaborating with cross-functional teams. Required qualifications include proficiency in model architecture design, experience with frameworks like PyTorch or TensorFlow, and strong problem-solving skills. Preferred qualifications include cloud deployment experience and familiarity with MLOps practices. The position offers weekly pay, professional growth investments, and comprehensive benefits.
Posted 2 weeks ago
AI/ML Engineer
HybridKallikor is seeking an AI/ML Engineer to develop domain-specific AI solutions for supply chain intelligence. This role focuses on building production-quality systems that integrate machine learning models into robust engineering frameworks. You will lead the architecture of our AI stack, working on FastAPI services, training pipelines, and model deployment. If you have a strong background in Python production systems along with experience in machine learning, this opportunity allows you to shape Project Genome and mentor junior engineers in a collaborative environment.
Posted 2 weeks ago
AI/ML Engineer
HybridImprobable is seeking an AI/ML Engineer to build and enhance AI-powered simulation digital twins for supply chain intelligence. This role focuses on creating a domain-specific language model and supporting Project Genome, aimed at synthesizing global supply chain knowledge. The ideal candidate will develop robust Python systems, deploy AI services, and integrate machine learning with existing infrastructure. A strong emphasis is placed on production engineering and maintaining high reliability in delivery.
Posted 2 weeks ago
AI/ML Engineer
RemoteXebia, a leading digital transformation partner, is seeking an AI/ML Engineer to design and implement AI solutions for clients across various sectors. The ideal candidate will have 3-6 years of experience in ML engineering, strong Python skills, and experience with cloud-based ML services. You will work on developing AI agents, building machine learning models, and collaborating with cross-functional teams. Xebia serves a wide array of clients, emphasizing engineering excellence and a people-first culture in a dynamic work environment.
Posted 3 weeks ago
How LiftmyCV Helps with AI Jobs Search
LiftmyCV combines AI matching, resume generation, and auto-apply to streamline every step of your ai jobs job search—from discovery to interview.
Discover AI Jobs Across 26,486+ Openings
AI scans millions of listings across 10+ job boards and surfaces the most relevant roles for your profile.
Learn more →Create Job-Specific Materials for AI Jobs Roles
Auto-generates tailored resumes and cover letters matched to each job description and ATS requirements.
Learn more →Auto-Apply and Automate AI Jobs Applications
Set your preferences and let the AI agent apply to matching jobs automatically, with full tracking and control.
Learn more →
AI Jobs Salary Data (June 2026)
This section summarizes salary information from 26,486+ active AI job postings, including roles across machine learning, research, data science, product, engineering, and applied AI functions where pay details are available.
Average Salary
$140k
$182k
$223k
25th
50th
75th
Based on 26,486 roles currently tracked by LiftmyCV. Last updated on Jun 6, 2026
Salary Distribution
Based on 26,486 roles currently tracked by LiftmyCV. Last updated on Jun 6, 2026
| Experience Level | 25th Percentile | Median (50th) | 75th Percentile | Sample Size |
|---|---|---|---|---|
| Overall | $140,000 | $182,250 | $223,489 | 12,732 |
| Entry-Level | $81,000 | $89,238 | $145,000 | 17 |
| Mid-Level | $142,800 | $176,000 | $225,000 | 98 |
| Senior-Level | $160,712.5 | $192,650 | $225,297.25 | 98 |
"AI jobs in 2026 are spreading across more than model research. I’m seeing employers separate pure machine learning work from AI product, data infrastructure, evaluation, safety, and applied engineering roles. The resume that works best is usually precise about the lane: what systems were built, what models or data pipelines were handled, and where the work moved from prototype to production. Vague AI enthusiasm doesn’t carry much weight once the interview loop starts."
Marina's Market Take
Senior HR Leader & Lead Tech Recruiter
How to Land an AI Job in 2026
AI jobs in 2026 cover several lanes, so your first task is to position yourself clearly. A machine learning engineer application should read differently from an AI product manager application, and both should look different from a data scientist, research scientist, MLOps engineer, or AI operations role. Employers reviewing AI candidates usually need to see where you fit in the workflow: building models, evaluating outputs, deploying systems, translating user needs, managing data pipelines, or improving applied AI products.
For technical AI roles, emphasize shipped work over vague model exposure. Point to projects where you trained, fine-tuned, evaluated, deployed, monitored, or improved AI systems. Name the tools and methods that match the role, such as Python, PyTorch, TensorFlow, SQL, vector databases, model evaluation, LLM workflows, retrieval systems, data labeling, or cloud deployment. If the role leans research, show publications, experiments, benchmarks, or applied prototypes. If it leans production, show reliability, latency, cost, monitoring, and handoff to engineering teams.
For non-engineering AI roles, make the connection between AI systems and business use cases explicit. AI product managers should show product judgment, roadmap tradeoffs, customer discovery, experimentation, and collaboration with data or engineering teams. AI analysts and operations candidates should highlight workflow design, quality review, prompt testing, documentation, vendor evaluation, and measurable process improvements. The most useful applications make it easy to see the AI problem, the tools involved, your role, and the result.
- Pick a lane: target titles that match your strongest evidence, such as machine learning engineer, AI product manager, data scientist, research scientist, MLOps engineer, or AI operations specialist.
- Match the posting’s AI stack: mirror the listed tools, model types, deployment environment, and evaluation requirements only when you have real experience with them.
- Prioritize applied proof: link to projects, case studies, demos, papers, GitHub work, or product launches that show how you used AI in practice.
LiftmyCV helps you find AI jobs that match your skills, experience, and preferred work style, then auto-apply to relevant roles faster.
Required Skills
Resume Tips
For AI jobs, keep the resume centered on the kind of AI work you actually do. Machine learning engineers should show model deployment, Python, PyTorch, TensorFlow, Docker, cloud platforms, and MLOps tools such as MLflow or Kubernetes. Data scientists should emphasize experimentation, SQL, feature work, evaluation methods, and business-facing analysis. AI product managers can lead with model-enabled product launches, user workflows, risk tradeoffs, and cross-functional delivery. Governance, safety, and compliance candidates should show policy reviews, audit support, model documentation, privacy work, or controls tied to AI systems.
Cut vague claims like “passionate about artificial intelligence,” long coursework lists, and tool dumps that aren’t connected to projects. If you mention LLMs, RAG, vector databases, prompt evaluation, LangChain, OpenAI API, Hugging Face, AWS, Azure, or GCP, connect each one to a shipped project, research result, production workflow, or measurable decision.
- Weak: “Worked on AI models and helped improve performance.”
- Strong: “Built a PyTorch classification model, improved F1 score from 0.71 to 0.82, and deployed batch inference with Docker for weekly operations reporting.”
Certifications such as AWS Machine Learning, Google Professional Machine Learning Engineer, Azure AI Engineer, or security and privacy credentials can help when they support the job description, but they shouldn’t replace project evidence. LiftmyCV helps you create an ATS-friendly AI jobs resume tailored to each job, so your skills and experience better match what employers are looking for.
How to Prepare for Interviews
AI job interviews in 2026 can vary sharply by lane, so prepare around the work you actually want to do. For machine learning engineering, expect technical screens on Python, model evaluation, data pipelines, and tradeoffs between accuracy, latency, and cost. A common format is a system design prompt such as designing a retrieval-augmented search feature, then explaining data flow, model choice, monitoring, and failure modes.
For applied research or data science roles, build examples around experiments, baselines, metrics, and why a model did or didn’t improve production outcomes. Product, operations, and compliance-focused AI roles may lean on case prompts: evaluating an AI feature, writing an adoption plan, reviewing model risk, or explaining policy constraints to non-technical stakeholders.
Bring specific project stories with measurable context: dataset size, evaluation metric, deployment environment, annotation workflow, or business constraint. If you have a portfolio, include notebooks, demos, model cards, case studies, or architecture diagrams that show judgment, not just polished outputs.