> Markdown version of [/jobs/ext/2551988-senior-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/2551988-senior-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** Censys, Inc. - **Location:** Ann Arbor, MI, United States - **Experience:** Expert - **Salary:** $174,000.0 - $206,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Computer Programming, Python (Programming Language), Machine Learning, Software Engineering, Google Cloud, Model Validation, Containerization, Kubernetes, Machine Learning Operations, Data Pipelines, Unsupervised Learning - **Published:** August 28, 2026 - **Apply:** https://www.dice.com/job-detail/fd58465e-1946-493f-83f8-3ccfe4906aa1 ## About the Role * 5+ years of experience in data science, machine learning engineering, or software engineering with applied ML responsibilities. * Experience building and deploying machine learning or statistical models in production environments. * Experience programming in Go/Python, and familiarity with software engineering practices for building maintainable systems. * Experience working with large datasets and building data pipelines for feature generation, training, or inference. * Proficiency with supervised and unsupervised learning techniques, such as classification, clustering, similarity scoring, or anomaly detection. * Ability to evaluate models using sound statistics and understand tradeoffs related to precision, recall, accuracy, and confidence. * Ability to write understandable, testable code with an eye towards maintainability * Possess strong communication skills and can explain technical concepts, model behavior, and tradeoffs to engineers, researchers, and product managers. Things that make you stand out: * Experience building classification, enrichment, or labeling systems for messy or partially labeled data. * Experience deploying models in containerized environments, like Kubernetes. * Experience with at least one cloud provider, like: AWS, Azure, or Google Cloud Platform. * Familiarity with feature stores, model serving, MLOps workflows, or tools for experiment tracking. * Familiarity with security, Internet measurement, or network-derived datasets. ## Description * Build and improve machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets and services. * Own the design and development of applied ML workflows that turn raw Internet telemetry into usable context for internal systems and customer-facing products. * Partner with engineering, research, security, and product teams to ensure we're building the right models, datasets, and feedback loops to improve coverage and quality. * Leverage your experience in machine learning, data science, and software engineering to build various parts of the system, including components like: feature pipelines, training datasets, model evaluation frameworks, confidence scoring systems, and services that run in the cloud or on-prem., To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates to keep their cameras on during video interviews. Additionally, if hired, we would love to bring you to our HQ in Ann Arbor for in-person onboarding., Pursuant to the California Consumer Privacy Act (CCPA), we are providing you with notice that we collect personal information from job applicants for business purposes, including evaluating your candidacy for employment, conducting interviews, and, if applicable, completing the hiring process. The categories of information we may collect include identifiers (such as name and contact information), professional or employment-related information (such as work history, education, and references), and other information you provide in your application. We do not sell or share your personal information. For more information on how we use and protect your personal information, and your rights under the CCPA, please refer to our Privacy Policy. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Machine Learning for Software Developers (and Knitters)](https://www.wearedevelopers.com/videos/154-machine-learning-for-software-developers-and-knitters) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? 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