Most In Demand STEM Jobs in the United States

Explore remote, full-time STEM roles in the United States on Rex.zone, focused on high-demand engineering and AI/ML workflows. These roles map to search-recognizable job entities (e.g., software engineer, data scientist, machine learning engineer, cybersecurity engineer, cloud engineer) and connect directly to real production pipelines: large language model evaluation, RLHF, training data quality, data labeling, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. If you build, test, secure, or scale AI systems, this page helps you match skills to hiring demand and apply through Rex.zone.

Machine Learning Engineer

LinkedIn Job Metadata: Title + Machine Learning Engineer | Date + 25-02-2026 | Company + Rexzone | Country + US | Remote Type + Remote | Employment Type + FULL_TIME | Experience Level + Mid-Senior | Industry + Technology | Job Function + Engineering | Skills + Machine learning, Deep learning, LLM training pipelines, RLHF, Model evaluation, Prompt evaluation, Python, PyTorch, TensorFlow, MLOps, Data labeling, QA evaluation | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR Role Overview: Build and deploy ML systems that improve model performance in real-world products. You will design training and evaluation workflows, integrate human feedback signals (RLHF) where applicable, and partner with data operations to ensure training data quality. Key Responsibilities: ["Design, train, and tune models for NLP and computer vision use cases", "Define offline and online evaluation strategies to measure model performance improvement", "Collaborate with annotation teams on annotation guidelines compliance and label taxonomy", "Implement prompt evaluation and QA evaluation loops for LLM behavior", "Improve dataset curation, data labeling throughput, and error analysis", "Ship models using MLOps practices (CI/CD, monitoring, drift detection)"] Preferred Background: ["Experience with LLMs, RLHF, and large language model evaluation", "Strong Python and deep learning frameworks (PyTorch/TensorFlow)", "Hands-on experience with training data pipelines, feature stores, and model monitoring", "Familiarity with NER, content safety labeling, or computer vision annotation"]

Data Scientist

LinkedIn Job Metadata: Title + Data Scientist | Date + 25-02-2026 | Company + Rexzone | Country + US | Remote Type + Remote | Employment Type + FULL_TIME | Experience Level + Mid-Senior | Industry + Technology | Job Function + Engineering | Skills + Data science, Statistical modeling, Experiment design, A/B testing, SQL, Python, Machine learning, Model evaluation, Data quality, NLP analytics, Training data quality, QA evaluation | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR Role Overview: Own analytical problem-solving across product and ML initiatives, connecting data quality to measurable outcomes. You will help define evaluation metrics, validate model improvements, and support LLM training pipelines with robust measurement. Key Responsibilities: ["Develop statistical models and dashboards to track model and product KPIs", "Design experiments (A/B tests) and interpret impact on user outcomes", "Partner with ML engineers to create model evaluation and error analysis plans", "Audit training data quality and identify label noise or sampling bias", "Support NLP evaluation, prompt evaluation, and QA evaluation reporting", "Translate findings into actionable recommendations for engineering teams"] Preferred Background: ["Strong SQL and Python analytics", "Experience with causal inference or experiment design", "Familiarity with ML evaluation metrics and dataset auditing", "Exposure to annotation workflows, NER, or content safety labeling is a plus"]

Software Engineer

LinkedIn Job Metadata: Title + Software Engineer | Date + 25-02-2026 | Company + Rexzone | Country + US | Remote Type + Remote | Employment Type + FULL_TIME | Experience Level + Mid-Senior | Industry + Technology | Job Function + Engineering | Skills + Software engineering, Distributed systems, APIs, Cloud infrastructure, Python, Java, System design, Data pipelines, MLOps, Observability, QA automation, Security best practices | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR Role Overview: Build reliable services and platforms that power modern ML and product systems. You will enable data pipelines, evaluation tooling, and scalable infrastructure used by AI/ML teams and data operations. Key Responsibilities: ["Design and implement backend services and APIs for data and model workflows", "Build scalable data pipelines supporting training and evaluation workloads", "Improve system design, reliability, and observability (logs, metrics, tracing)", "Integrate QA automation and testing strategies for production readiness", "Collaborate with ML teams on MLOps integrations and deployment patterns", "Harden services with security best practices and access controls"] Preferred Background: ["Experience with distributed systems and cloud-native development", "Strong coding in Python/Java and service ownership", "Familiarity with MLOps concepts and ML evaluation tooling", "Exposure to annotation platforms or model evaluation pipelines is a plus"]

Cybersecurity Engineer

LinkedIn Job Metadata: Title + Cybersecurity Engineer | Date + 25-02-2026 | Company + Rexzone | Country + US | Remote Type + Remote | Employment Type + FULL_TIME | Experience Level + Mid-Senior | Industry + Technology | Job Function + Engineering | Skills + Cybersecurity, Threat modeling, Incident response, Cloud security, IAM, Security monitoring, Vulnerability management, Zero trust, Secure SDLC, SIEM, Compliance, Risk assessment | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR Role Overview: Protect systems, data, and ML platforms with modern security engineering practices. You will secure cloud environments, reduce risk in the software lifecycle, and strengthen monitoring and incident response. Key Responsibilities: ["Implement threat modeling and security architecture reviews", "Build and tune security monitoring (SIEM) and alerting pipelines", "Lead incident response, postmortems, and remediation tracking", "Harden IAM, secrets management, and access control policies", "Drive vulnerability management and secure SDLC practices", "Partner with engineering to meet compliance and risk requirements"] Preferred Background: ["Strong cloud security and IAM experience", "Hands-on incident response and detection engineering", "Familiarity with zero trust and secure SDLC", "Experience supporting AI/ML platforms is a plus"]

Cloud Engineer

LinkedIn Job Metadata: Title + Cloud Engineer | Date + 25-02-2026 | Company + Rexzone | Country + US | Remote Type + Remote | Employment Type + FULL_TIME | Experience Level + Mid-Senior | Industry + Technology | Job Function + Engineering | Skills + Cloud engineering, AWS, Azure, GCP, Infrastructure as code, Kubernetes, CI/CD, Networking, Observability, Cost optimization, Security best practices, Data pipelines | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR Role Overview: Build and operate cloud infrastructure that supports scalable applications and ML workloads. You will enable reliable environments for training data pipelines, model evaluation, and production services. Key Responsibilities: ["Design and manage cloud infrastructure across compute, storage, and networking", "Automate provisioning using infrastructure as code and CI/CD", "Operate Kubernetes and containerized services for scalable workloads", "Implement observability and SRE practices (SLIs/SLOs, on-call readiness)", "Optimize cloud cost and performance for data and ML workloads", "Apply security best practices across cloud environments"] Preferred Background: ["Hands-on experience in AWS/Azure/GCP", "Kubernetes and IaC expertise", "Experience supporting data pipelines or MLOps infrastructure", "Strong debugging, reliability, and cost optimization skills"]

Data Engineer

LinkedIn Job Metadata: Title + Data Engineer | Date + 25-02-2026 | Company + Rexzone | Country + US | Remote Type + Remote | Employment Type + FULL_TIME | Experience Level + Mid-Senior | Industry + Technology | Job Function + Engineering | Skills + Data engineering, ETL, SQL, Python, Data pipelines, Data modeling, Spark, Warehousing, Data quality, Metadata management, Training data quality, Annotation workflows | Salary Currency + USD | Salary Min + 63360 | Salary Max + 126720 | Pay Period + YEAR Role Overview: Build data pipelines that power analytics and AI. You will improve training data quality, enable scalable ingestion and transformation, and support annotation workflows that feed LLM training pipelines. Key Responsibilities: ["Develop ETL/ELT pipelines for structured and unstructured data", "Implement data quality checks, anomaly detection, and lineage tracking", "Model data for warehouse/lakehouse consumption and ML features", "Support dataset curation for ML teams, including sampling and deduplication", "Enable metadata management and governance for sensitive data", "Collaborate with annotation teams on data labeling inputs and outputs"] Preferred Background: ["Strong SQL and Python; experience with Spark", "Hands-on pipeline orchestration and warehouse/lakehouse design", "Experience with training data quality and dataset versioning", "Familiarity with annotation workflows or NER is a plus"]

Frequently Asked Questions

Q: What are the most in demand STEM jobs in the United States?
Common high-demand STEM roles include Machine Learning Engineer, Data Scientist, Software Engineer, Cybersecurity Engineer, Cloud Engineer, and Data Engineer. Demand is driven by cloud adoption, security needs, and AI/ML productization, including LLM training pipelines and model evaluation.
Q: Are these roles remote and full-time?
Yes. Each role on this page is listed as Remote and FULL_TIME in the LinkedIn-compatible job metadata.
Q: How do AI/ML concepts like RLHF and data labeling relate to STEM hiring demand?
Many engineering teams now rely on human-in-the-loop workflows to improve model performance, including RLHF, data labeling, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling. These workflows increase demand for engineers who can build reliable data and evaluation pipelines.
Q: What skills should I highlight to be competitive for these STEM jobs?
Highlight job-relevant skills such as Python, SQL, system design, cloud platforms (AWS/Azure/GCP), MLOps, security fundamentals, distributed systems, experiment design, and model evaluation. If applying to AI/ML-adjacent roles, emphasize training data quality, annotation guidelines compliance, and large language model evaluation.
Q: Where do I apply for these roles?
Apply via Rex.zone by selecting the role that best matches your experience and skills, then following the application workflow for that posting.
Q: Do you offer contract or freelance options too?
Rex.zone may list remote contract or freelance roles in addition to full-time roles. This page focuses on Remote FULL_TIME postings, but you can search Rex.zone using modifiers like contract, freelance, entry-level, or senior to find additional options.

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