15,682 Machine Learning Engineer Jobs (June 2026)
Machine learning engineer roles in June 2026 commonly center on model development, data pipelines, experimentation, and production ML systems. Listings may span applied ML, MLOps, recommendation systems, NLP, computer vision, and platform-focused engineering work across remote, hybrid, and on-site teams. Create an account to explore the full job feed and auto-apply with LiftmyCV AI Agent.
Staff Machine Learning Engineer, ML Infrastructure
HybridSimpliSafe is seeking a Staff Machine Learning Engineer to join its Cloud ML team. This key role focuses on building and operating ML infrastructure, driving architecture, and mentoring colleagues. The ideal candidate will have significant experience in developing production ML systems and will be responsible for enhancing the company's platforms for real-time computer vision and GenAI applications. The position offers opportunities for professional growth in a collaborative environment, embracing a hybrid work model.
Posted 1 week ago
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Principal Machine Learning Engineer
ANYThe Principal Machine Learning Engineer role at Doctolib involves designing and implementing advanced machine learning models to enhance healthcare solutions. Candidates should have a strong background in data analysis, machine learning algorithms, and software engineering practices. The position focuses on building innovative AI-driven tools, collaborating closely with cross-functional teams to ensure the successful application of machine learning in healthcare contexts.
Posted 2 days ago
Principal Machine Learning Engineer
HybridMedical Guardian is seeking a Principal Machine Learning Engineer to lead hands-on initiatives in machine learning and applied AI. This role focuses on developing, validating, and deploying predictive models while operating with a high degree of technical judgment. Key responsibilities include model development, stakeholder engagement, and ensuring operational readiness. Ideal candidates should bring extensive experience in machine learning, strong technical skills, and the ability to translate unclear problems into actionable solutions. Experience with modern ML platforms and a collaborative mindset are essential for success in this role.
Posted 1 week ago
Principal Machine Learning Engineer
HybridJoin Headspace as a Principal Machine Learning Engineer to lead the development of innovative AI solutions aimed at enhancing mental healthcare. You'll create and deploy advanced language-based machine learning applications, manage scalable AI projects, and collaborate with cross-functional teams, all while inspiring technical growth among peers. With 8+ years of experience in machine learning and a Master's degree or equivalent, your expertise will help shape the future of mental health support. This role offers a competitive salary, equity, and comprehensive benefits in a mission-driven organization.
Posted 3 weeks ago
Junior Machine Learning Engineer
HybridENSCO, Inc. is looking for a Junior Machine Learning Engineer to join their team. This role involves working with Machine Learning (ML) and Deep Learning (DL) models, collaborating with senior scientists to solve complex problems. The ideal candidate should have a degree in a relevant field and a minimum of two years of industry experience. Additional qualifications such as advanced proficiency in data science languages and the ability to obtain a U.S. security clearance are required. This hybrid position offers a competitive salary and benefits.
Posted 1 week ago
Staff Machine Learning Engineer
On-siteLucid Motors is redefining the luxury electric vehicle experience with advanced technology and design. We are seeking a Staff Software Engineer to focus on integrating and deploying perception models for our ADAS and autonomous driving systems. This role will involve collaboration with ML researchers and engineers to deliver high-performance solutions, optimize performance, and develop automated pipelines. Candidates should have a strong background in software engineering and proficiency in C++ and Python, with significant experience in perception systems.
Posted 2 days ago
Staff Machine Learning Engineer
On-siteCohere Health is seeking a Staff Machine Learning Engineer to lead technical initiatives within their Enterprise ML team. The role focuses on enhancing machine learning capabilities for their Intake product, employing advanced techniques to automate workflows and improve data quality. Collaborating with various teams, the engineer will contribute to significant ML projects while also mentoring junior engineers. Candidates should possess a Master’s degree (PhD preferred), over 7 years of experience in applied machine learning, and deep expertise in Python and ML frameworks. The ideal applicant must have experience deploying production ML systems in healthcare settings.
Posted 2 weeks ago
Staff Machine Learning Engineer
RemoteAs a Staff Machine Learning Engineer at Material Security, you'll join a team dedicated to enhancing user privacy and security. Your primary focus will be on developing, deploying, and maintaining advanced machine learning models aimed at identifying sensitive information and malicious behaviors, such as phishing attacks. You will collaborate with cross-functional teams, utilize recent advancements in generative AI, and contribute to a robust engineering culture while ensuring high model performance and reliability.
Posted 2 weeks ago
Staff Machine Learning Engineer
HybridOrbem is seeking a Staff Machine Learning Engineer to lead the development of intelligent systems for next-generation MRI technology. In this role, you will design scalable ML solutions, collaborating closely with data scientists and engineers to impact healthcare positively. Your expertise in ML system design, along with your passion for innovation and excellence, will help elevate Orbem to a Machine Learning powerhouse. Join our diverse team and play a crucial role in transforming biological insights into actionable intelligence for a sustainable future.
Posted 3 weeks ago
Lead Machine Learning Engineer
On-siteAbbVie seeks a Lead Machine Learning Engineer at Allergan Aesthetics to collaborate with cross-functional teams in developing and managing data and machine learning products. The position involves technical leadership, system architecture, and innovation in ML and AI solutions. Candidates should have a strong background in machine learning, programming in Python, and experience with relevant frameworks and tools. The role offers opportunities for mentorship and the integration of innovative approaches in the broader ML engineering community.
Posted 3 days ago
Senior Machine Learning Engineer
ANYdoctolib is seeking a Senior Machine Learning Engineer to enhance their AI-driven healthcare platform. The role requires a strong foundation in machine learning algorithms, data processing, and deployment of models. Ideal candidates should have experience with Python and relevant frameworks, as well as a passion for improving healthcare outcomes. The position offers opportunities to impact the lives of patients through innovative technologies.
Posted today
Senior Machine Learning Engineer
On-siteJoin Rockstar Games as a Senior Machine Learning Engineer, where you'll influence game design and player engagement using cutting-edge data science techniques. This full-time position emphasizes robust machine learning solutions in a collaborative environment, leveraging insights for improved gaming experiences. Your expertise will directly contribute to innovative data pipelines and machine learning applications, supporting a forward-thinking team in a dynamic industry.
Posted 2 days ago
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Machine Learning Engineer Salary Data (June 2026)
This salary section summarizes pay information from 15,682+ active Machine Learning Engineer postings, including roles focused on model development, production ML systems, and applied machine learning work.
Average Salary
$170k
$201k
$233k
25th
50th
75th
Based on 15,682 roles currently tracked by LiftmyCV. Last updated on May 7, 2026
Salary Distribution
Based on 15,682 roles currently tracked by LiftmyCV. Last updated on May 7, 2026
| Experience Level | 25th Percentile | Median (50th) | 75th Percentile | Sample Size |
|---|---|---|---|---|
| Overall | $169,750 | $201,250 | $232,750 | 7,446 |
| Entry-Level | $78,000 | $101,100 | $118,300 | 4 |
| Mid-Level | $150,000 | $195,000 | $221,950 | 37 |
| Senior-Level | $184,500 | $212,500 | $236,525 | 71 |
"Machine Learning Engineer hiring in 2026 tends to split between people who can train models and people who can ship them. Teams are paying closer attention to production judgment: data pipelines, evaluation, latency, monitoring, and how a model behaves after release. Research depth still matters for some openings, but many ML Engineer roles now read closer to software engineering jobs with serious model fluency layered in."
Marina's Market Take
Senior HR Leader & Lead Tech Recruiter
How to Land a Machine Learning Engineer Job in 2026
Machine learning engineer jobs in 2026 usually reward candidates who can connect model work to production systems. Your application should make the lane clear: training and evaluating models, deploying inference services, improving data pipelines, optimizing LLM or recommendation workflows, or maintaining ML infrastructure. A vague “ML projects” summary is weaker than showing the exact model type, data scale, deployment pattern, and business or product problem you handled.
For applied machine learning engineer roles, emphasize shipped systems over notebooks. Include examples of model selection, feature engineering, evaluation metrics, experiment tracking, latency tradeoffs, monitoring, and retraining. If your work involved Python, PyTorch, TensorFlow, scikit-learn, Spark, Kubernetes, Airflow, or cloud ML services, place those tools near the project where you used them. Recruiters and technical screeners should be able to see how you moved from training data to a usable model endpoint.
For LLM-focused machine learning engineer jobs, be precise about your role in retrieval, fine-tuning, prompt evaluation, embeddings, ranking, guardrails, or model serving. If you built RAG pipelines, mention the vector database, chunking strategy, evaluation method, and how you tested answer quality. If you worked on traditional ML, don’t force an LLM angle. Position yourself around forecasting, classification, ranking, personalization, computer vision, NLP, or anomaly detection based on the strongest evidence in your background.
- Application positioning: Lead with 2 to 4 production ML projects, including model type, stack, evaluation metric, and deployment environment.
- Search strategy: Separate ML engineer, applied scientist, MLOps engineer, LLM engineer, and data scientist listings so you apply where your evidence fits the job scope.
- Interview prep: Be ready to discuss tradeoffs around data leakage, model drift, offline versus online metrics, latency, cost, and failure modes.
LiftmyCV helps you find 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 machine learning engineer roles, your resume should show that you can move models from experimentation into usable systems. Highlight Python, SQL, PyTorch, TensorFlow, scikit-learn, feature engineering, model evaluation, deployment, data pipelines, and cloud work in AWS, GCP, or Azure. If you’ve used MLflow, Airflow, Spark, Docker, Kubernetes, SageMaker, Vertex AI, or Databricks, place those tools near the projects where they were actually used.
Cut coursework-heavy descriptions once you have production or applied project experience. A long list of algorithms is less useful than proof that you improved latency, reduced false positives, automated retraining, monitored drift, or shipped a recommendation, ranking, forecasting, NLP, or computer vision model. Certifications can help when they’re relevant, such as AWS Machine Learning, Google Professional Machine Learning Engineer, or Databricks credentials, but they shouldn’t replace project outcomes.
- Weak bullet: “Built machine learning models using Python and TensorFlow.”
- Strong bullet: “Developed a TensorFlow ranking model for product search, improved offline NDCG by 12%, containerized inference with Docker, and deployed batch scoring through Airflow on AWS.”
Present each role with a clear split between data, modeling, and engineering ownership. If your experience is research-heavy, translate papers and experiments into measurable systems work, such as benchmarks, reproducible pipelines, or model serving in 2026. 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
Interview prep for machine learning engineer roles
Machine learning engineer interviews usually test both modeling judgment and production engineering. Prepare to explain one deployed model from your resume: the dataset, feature choices, validation method, offline metric, production metric, latency constraint, and what changed after launch. A useful 2026 example might cover reducing false positives in a classification model, improving retrieval quality, or monitoring drift after a recommendation model shipped.
Expect a mix of coding screens, ML fundamentals, and system design. One common prompt is: design a real-time fraud detection system, then discuss data freshness, feature stores, model retraining, evaluation, and failure modes. You may also see questions on bias-variance tradeoffs, embeddings, gradient boosting versus neural networks, A/B testing, or debugging a model whose validation score is high but production performance is poor.
Review your Python, SQL, data pipelines, experiment tracking, and cloud deployment details. Bring concise stories about messy labels, scaling inference, model monitoring, and tradeoffs you made when accuracy, cost, and interpretability pulled in different directions.