33,362 Verified Artificial Intelligence (AI) Jobs - July 2026
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.
AI and Machine Learning Engineer
On-siteMitsubishi Power EMEA is looking for a motivated AI and Machine Learning Engineer to join their Engineering team. Ideal for recent Master's graduates, this role involves applying AI techniques to tackle real-world challenges in power generation. Working with a Principal Engineer, you will develop digital solutions for turbine operations, gaining hands-on experience while contributing to innovative AI-driven projects that enhance performance and reliability.
Posted 6 days ago
AI / Machine Learning Engineer
On-siteJoin InstantServe and make a significant impact on healthcare by working on innovative AI solutions for international clients. Enjoy a dynamic work environment with competitive salary and professional growth opportunities. We value confidentiality and adhere to EEO guidelines.
Posted 1 week ago
AI/Machine Learning Engineer
RemoteMoonshot is seeking a passionate AI/Machine Learning Engineer to join their growing team. This role focuses on tackling online harms including violent extremism and child exploitation. The ideal candidate will work closely with the Director of Engineering to build high-quality, user-focused software systems. Responsibilities include developing ML models, integrating them into products, and ensuring continuous improvement. Moonshot values diversity and encourages applications from underrepresented communities. Join us in making a meaningful impact through technology.
Posted 1 week ago
AI/Machine Learning Engineer
HybridTechconnect.id is seeking an AI/Machine Learning Engineer to lead the design, development, and deployment of AI systems and ML models. This role focuses on aligning technical strategies with business objectives, mentoring junior engineers, and ensuring seamless integration of AI capabilities into products. Opportunities exist for both senior-level leadership and mid/junior-level support roles within a collaborative environment. The ideal candidate will have strong technical expertise, excellent problem-solving skills, and the ability to work in a hybrid setup.
Posted 2 weeks ago
AI and Machine Learning Engineer
On-siteHewlett Packard Enterprise is seeking a Senior AI/ML & Innovation Engineer for their Hybrid Cloud portfolio. This role, designed as 'Hybrid', demands strong expertise in machine learning and software development. The engineer will lead initiatives to improve product performance and translate customer requirements into innovative AI/ML solutions. The ideal candidate will have a background in computer science or related fields, with 4-7 years of experience in machine learning algorithms, programming, and statistical modeling. They will also foster collaboration within cross-functional teams and stay updated on new technologies.
Posted 3 weeks ago
AI & Machine Learning Engineer
On-siteThe AI & Machine Learning Engineer role involves designing and developing integrated AI systems and implementing machine learning algorithms. Based in Athens, Greece, the position focuses on collaboration within interdisciplinary teams to create efficient applications in AI and Finance. Responsibilities include developing AI solutions, working with large language models, refining prompt engineering techniques, and utilizing APIs to enhance intelligent solutions while staying updated on field developments.
Posted 3 weeks ago
AI Architect (Applied AI Engineer)
RemoteMisfits & Machines is seeking an AI Architect to design and build AI systems for their generative video platform. The ideal candidate will work closely with creative and product teams to translate ideas into working systems. Responsibilities include creating AI agent workflows, crafting intelligence, managing observability, and making architectural decisions. Candidates should have over five years of software engineering experience, particularly in LLM systems, and proficiency in TypeScript/JavaScript. The role focuses on practical implementation rather than management or pure research.
Posted 1 day ago
Machine Learning Engineer/AI Engineer (Infra)
On-siteSertis, located in Bangkok, is an industry leader in Data and AI solutions, serving various sectors including retail, finance, and healthcare. The Machine Learning Engineer role requires a strong background in AI/ML engineering, focusing on optimizing models and building robust MLOps infrastructure. Ideal candidates will have experience in cloud-based solutions, programming, and generative AI applications. The company prides itself on a culture of innovation and learning, aiming to deliver the best solutions in the Data and AI space.
Posted 6 days ago
Machine Learning Engineer, Applied AI
ANYIdeogram is seeking an Applied ML Engineer to bridge research and product by developing generative models into production features. The ideal candidate has at least a year of experience in building ML products, proficient in Python and familiar with modern deep learning techniques. You'll collaborate with teams to deploy models and ensure product success while embracing a culture of curiosity and shared ownership.
Posted 1 week ago
AI Prompt Engineer
On-siteThe AI Prompt Engineer is tasked with designing, testing, and optimizing prompt strategies to ensure large language models deliver accurate and safe outputs for various enterprise applications. This role requires collaboration with cross-functional teams to translate complex business needs into effective AI solutions while ensuring prompt quality and compliance with governance standards. Candidates should have experience with LLMs, strong communication abilities, and a background in relevant technical fields.
Posted 2 weeks ago
AI Prompt Engineer
On-siteVAM Systems is seeking an AI Prompt Engineer for their operations in Qatar. The ideal candidate will be responsible for designing prompts, testing outputs, defining grounding documents, and validating responses, contributing to the enhancement of AI-driven projects. The role requires a commitment to join within two weeks, extending to a maximum of one month.
Posted 4 weeks ago
AI & ML Engineer
HybridCharlotte Tilbury Beauty is seeking an AI & ML Engineer to join its innovative team. This role is crucial in driving the adoption of AI across the business by developing robust and scalable machine learning solutions. Responsibilities include designing AI systems, maintaining ML pipelines, and collaborating with cross-functional teams. Ideal candidates have strong Python skills, experience with GCP or equivalent platforms, and a good understanding of MLOps. Join a dynamic company that values creativity and teamwork, while being part of a growth-driven environment.
Posted 4 days ago
AI/ML Engineer
RemoteExpression is seeking an experienced AI/ML Engineer to design, optimize, and evaluate machine learning capabilities for heterogeneous edge computing platforms. The role involves developing AI pipelines for intelligent signal characterization, supporting decision-making within resource-constrained environments. Ideal candidates should have strong expertise in applied machine learning, edge AI optimization, and production deployment of AI systems. Security clearance eligibility is required. Expression prioritizes client engagement for tailor-made solutions and has been recognized as a top government contractor.
Posted 4 days ago
AI/ML Engineer
On-siteNode.Digital is seeking an AI/ML Engineer to support U.S. Government initiatives by automating machine learning integration activities. This role involves developing solutions to enhance workflow efficiency and data management, particularly in the realm of cyber-incident response and malware analysis. Candidates must have an active Top Secret Clearance and will play a crucial role in creating robust automation processes.
Posted 5 days ago
AI/ML Engineer
RemoteFuture Works is a US-focused, AI-native professional services firm specializing in operational AI and data systems. As an AI/ML Engineer, you will design and build AI agent systems for managing complex transaction workflows at a large enterprise. The role emphasizes building agent capabilities, developing tools and integrations, and ensuring quality testing across transaction stages. Candidates should have experience in software or machine learning engineering, solid Python skills, and familiarity with financial analytics and NLP. The company promotes a culture of freedom and high performance with numerous remote work benefits.
Posted 5 days ago
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AI Jobs Salary Data (July 2026)
This section summarizes salary information from 33,362+ 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
$133k
$177k
$223k
25th
50th
75th
Based on 33,362 roles currently tracked by LiftmyCV. Last updated on Jul 7, 2026
Salary Distribution
Based on 33,362 roles currently tracked by LiftmyCV. Last updated on Jul 7, 2026
| Experience Level | 25th Percentile | Median (50th) | 75th Percentile | Sample Size |
|---|---|---|---|---|
| Overall | $132,625 | $177,475 | $222,500 | 13,723 |
| Entry-Level | $116,887.5 | $142,900 | $169,862.5 | 8 |
| Mid-Level | $112,500 | $162,000 | $200,000 | 113 |
| Senior-Level | $158,304 | $201,150 | $234,185 | 111 |
"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.