7,160 Remote Machine Learning Engineer Jobs (May 2026)
Remote machine learning engineer roles in May 2026 often center on model development, production ML systems, data pipelines, evaluation workflows, and collaboration with software engineering or product teams across distributed environments. Candidates can expect listings that may span applied ML, MLOps, NLP, computer vision, recommendation systems, and backend-heavy machine learning work. Create an account to explore the full job feed and auto-apply with LiftmyCV AI Agent.
Principal Machine Learning Engineer
RemoteJoin A1, a pioneering team developing an AI system that comprehensively understands context and proactively plans actions over time. As a Principal Machine Learning Engineer, you will lead the implementation of production-grade machine learning systems, from training to deployment. You'll architect scalable inference systems and collaborate closely with application engineering teams to seamlessly integrate ML solutions. The role requires a strong background in deep learning and a hands-on approach to deploying large-scale ML models, with a commitment to quality and rapid iteration.
Posted 1 week ago
Staff Machine Learning Engineer
RemoteMaterial Security is seeking a Staff Machine Learning Engineer to join their team of experienced engineers. Your role will focus on building, deploying, and maintaining high-quality models that detect security threats such as phishing and sensitive data breaches. The ideal candidate will have extensive experience in machine learning, a strong understanding of data pipelines, and effective communication skills to collaborate across teams. This position is remote, allowing a flexible work environment while contributing to a diverse and inclusive culture.
Posted 2 days ago
Staff Machine Learning Engineer
RemoteA1 is developing a proactive AI chat app aimed at enhancing users' daily tasks through intelligent conversations and workflows. As the Technical Lead in Machine Learning, you will manage the execution layer of A1’s intelligence, focusing on translating research into scalable ML systems. Your responsibilities include overseeing data pipelines, training workflows, and production deployments. A collaborative approach with application engineering is essential, and you will work under real-world constraints to ensure efficiency and performance in production settings.
Posted 1 week ago
Staff Machine Learning Engineer
RemoteDragos, a leader in ICS/OT Cybersecurity, seeks a Staff Machine Learning Engineer. The role focuses on developing and implementing machine learning systems for enhancing threat detection and security analysis in industrial environments. The candidate will collaborate with a team of data professionals and contribute to the AI/ML capabilities of the Dragos platform, fostering a culture of authenticity, transparency, and trust. This remote position offers a competitive salary and comprehensive benefits, making it a prime opportunity for those passionate about cybersecurity and technology.
Posted 1 week ago
Senior Machine Learning Engineer
RemoteThoughtworks is seeking a Senior Machine Learning Engineer to build and manage architectures for machine learning applications. This role involves collaborating with data scientists, developing robust ML systems, and driving strategic initiatives. Candidates should possess strong experience in AI and LLMs, be proficient in scripting languages, and have a deep understanding of ML technologies. Thoughtworks values continuous learning, offering unique career development tools to support your growth in a dynamic and inclusive environment.
Posted today
Senior Machine Learning Engineer
RemoteHackerRank is seeking a Senior Machine Learning Engineer to develop innovative algorithms that enhance software development capabilities. This role involves working with cross-functional teams to solve complex problems using state-of-the-art techniques in machine learning and artificial intelligence. The ideal candidate will have strong analytical skills, experience with machine learning frameworks, and a passion for technology-driven solutions. Join HackerRank to be a part of an exciting journey in the tech industry.
Posted today
Senior Machine Learning Engineer
RemoteFullscript, an industry-leading health technology company, seeks a Senior Machine Learning Engineer to join its AI & Analytics Engineering team. This role involves building AI-driven lab interpretation and clinician support tools, collaborating closely with various stakeholders to enhance healthcare delivery. Ideal candidates will have over 5 years of experience in machine learning and backend engineering, particularly with LLM-powered applications. The position is remote-friendly, offering a competitive salary and various perks aimed at supporting employee well-being and professional growth.
Posted 2 days ago
Senior Machine Learning Engineer
RemoteCheckmate is revolutionizing restaurant technology by providing innovative solutions for digital ordering. As a Senior Machine Learning Engineer, you will play a key role in developing and deploying machine learning models that enhance voice ordering, prediction algorithms, and analytics. Join a team known for its adaptability and commitment to service, and make a meaningful impact within a collaborative environment that values ownership and drive.
Posted 3 days ago
Senior Machine Learning Engineer
RemoteOrita is seeking a Senior Machine Learning Engineer to design, train, and deploy models for marketing solutions. The role requires building scalable MLOps infrastructure and collaborating with cross-functional teams. Ideal candidates will have over five years of software engineering experience and expertise in modern ML algorithms. Familiarity with GCP and ML frameworks like PyTorch and TensorFlow is necessary. Applicants should possess strong communication skills and the ability to work in a fast-paced environment. Orita values ownership and continuous learning in its culture.
Posted 3 days ago
Senior Machine Learning Engineer
RemoteSpexi is seeking a Senior Machine Learning Engineer to advance their innovative drone-based geospatial imagery platform. This role involves leading model development for image classification, object detection, and predictive analytics. The engineer will bridge research and production, ensuring high-quality code for geospatial intelligence products. Responsibilities include designing scalable ML pipelines, collaborating with various teams, and maintaining geospatial accuracy. The ideal candidate has a strong background in machine learning and computer vision, ideally within geospatial contexts, and possesses experience transitioning models from research to production.
Posted 4 days ago
Senior Machine Learning Engineer
RemoteReal is seeking a Senior Machine Learning Engineer to join its R&D Team. Candidates should possess a strong foundation in machine learning and AI, specifically in Generative AI and LLM-driven applications. The role involves embedding AI solutions across various business facets, focusing on scalable system design and production deployment. Required skills include Python programming, experience with AI/ML applications, and the ability to communicate effectively with diverse teams. A minimum of 2 years of experience in production environments and 5 years in AI/ML is preferred.
Posted 5 days ago
Senior Machine Learning Engineer
RemoteInspiren is seeking a Senior Machine Learning Engineer to develop scalable workflows using cloud-based Vision-Language Models (VLMs). This role will encompass end-to-end pipeline management and collaboration with various teams to enhance VLM performance through signal determination, labeling, and integration of commercial models. Candidates should have significant experience in machine learning engineering, particularly in computer vision and VLM systems, as well as strong collaboration and communication skills. The position offers a flexible work environment with a competitive salary package.
Posted 1 week ago
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Remote Machine Learning Engineer Salary Data (May 2026)
This section summarizes salary information from 7,160+ active remote machine learning engineer postings, including roles focused on model development, ML systems, and production deployment. Use it to compare compensation signals across remote openings before you apply.
Average Salary
$153k
$198k
$238k
25th
50th
75th
Based on 7,160 roles currently tracked by LiftmyCV. Last updated on May 7, 2026
Salary Distribution
Based on 7,160 roles currently tracked by LiftmyCV. Last updated on May 7, 2026
| Experience Level | 25th Percentile | Median (50th) | 75th Percentile | Sample Size |
|---|---|---|---|---|
| Overall | $152,750 | $197,950 | $237,500 | 711 |
| Entry-Level | $73,880 | $104,200 | $135,000 | 11 |
| Mid-Level | $150,000 | $185,000 | $222,812.5 | 76 |
| Senior-Level | $167,250 | $215,250 | $247,512.5 | 128 |
"Remote Machine Learning Engineer hiring in 2026 tends to reward engineers who can show production judgment, not just model experimentation. Teams are often sorting for people who can work across data pipelines, model deployment, evaluation, and cloud infrastructure without needing constant in-person coordination. For remote ML roles, clear evidence of shipped systems, reproducible workflows, and async communication usually carries more weight than a long list of frameworks."
Marina's Market Take
Senior HR Leader & Lead Tech Recruiter
How to Land a Remote Machine Learning Engineer Role in 2026
Remote machine learning engineer jobs usually reward candidates who can show production judgment, not only model-building ability. In 2026, your positioning should make it clear where you fit: applied ML, ML platform, computer vision, NLP, recommendation systems, forecasting, LLM applications, or MLOps. A remote employer has less room for vague claims, so your application should connect specific models, data pipelines, deployment choices, and business-facing outcomes in a way that a distributed engineering team can evaluate quickly.
For applied ML roles, emphasize shipped models, feature engineering, experimentation, model evaluation, and how you handled messy production data. For ML platform or MLOps roles, lead with model serving, monitoring, CI/CD for ML workflows, orchestration, cloud infrastructure, and reliability work. If your background includes LLMs, name the actual work: retrieval, fine-tuning, evaluation, prompt systems, safety checks, latency reduction, or cost control. Remote teams also care about written technical clarity, so include examples of design docs, async collaboration, code reviews, or cross-functional work with product and data teams.
- Choose a lane before applying. A resume aimed at every remote machine learning engineer opening often reads too broad. Match your top projects to the role’s center of gravity, such as NLP systems, ranking models, ML infrastructure, or computer vision pipelines.
- Show production ownership. Mention deployment environments, model monitoring, data validation, retraining workflows, APIs, batch jobs, or cloud services when they apply.
- Make remote readiness concrete. Reference async design discussions, documentation habits, distributed sprint work, or collaboration across time zones if those were part of your previous engineering work.
- Search with technical filters. Prioritize listings that match your stack, such as Python, PyTorch, TensorFlow, scikit-learn, Spark, Kubernetes, AWS, GCP, Azure, MLflow, Airflow, or vector databases.
LiftmyCV helps you find remote machine learning engineer jobs that match your skills, experience, and preferred work style, then auto-apply to relevant roles faster.
Required Skills
Resume Tips
For remote machine learning engineer roles, your resume should show that you can build models that survive outside notebooks. Lead with production ML work: model training, feature engineering, evaluation, deployment, monitoring, and retraining. Mention concrete tools such as Python, PyTorch, TensorFlow, scikit-learn, SQL, Spark, MLflow, Airflow, Docker, Kubernetes, AWS, GCP, Azure, Databricks, and vector databases when they match your experience.
Cut vague research summaries, long coursework sections, and tool lists that are not connected to shipped work. A remote ML engineer resume should also show async collaboration: clear technical docs, experiment tracking, code reviews, RFCs, cross-functional work with product or data teams, and ownership across time zones. If you have an AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, or Databricks certification, include it, but do not let credentials replace project proof.
- Weak bullet: “Built machine learning models to improve recommendations.”
- Stronger bullet: “Trained and deployed a PyTorch ranking model for product recommendations, using MLflow for experiment tracking and Airflow pipelines to refresh features weekly.”
Present recent work first, especially projects active in 2026. If you include academic ML projects, frame them around datasets, evaluation metrics, deployment constraints, and reproducible code rather than class names alone. LiftmyCV helps you create an ATS-friendly machine learning engineer resume tailored to each job, so your skills and experience better match what employers are looking for.
How to Prepare for Interviews
Remote machine learning engineer interviews usually test whether you can move from model idea to production behavior without relying on in-person handoffs. Prepare to discuss feature design, model evaluation, data leakage, experiment tracking, deployment tradeoffs, and how you debug drift or latency after release. For 2026, keep examples grounded in actual ML systems, not just notebooks.
Expect a mix of formats: a coding screen in Python, a machine learning fundamentals discussion, and a system design prompt such as, “Design a recommendation model for a remote-first marketplace and explain how you would measure success.” Practice walking through data inputs, baseline models, offline metrics, online tests, monitoring, and rollback plans.
Bring two or three project stories with numbers attached: model lift, inference cost reduction, labeling improvements, false positive changes, or pipeline runtime cuts. If you have a portfolio, make it easy to review with clear README files, reproducible experiments, and notes on remote collaboration through pull requests, design docs, or async reviews.