Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4341762725&distance=25&f_AL=true&f_TPR=r86400&f_WT=2&geoId=103644278&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER&refresh=true&spellCorrectionEnabled=true Job Description: CyberWinter Studios Share Show more options Machine Learning & Data Science Engineer (Remote – U.S.) United States · 20 minutes ago · 11 applicants No response insights available yet Remote Matches your job preferences, workplace type is Remote. Full-time Easy Apply Save Save Machine Learning & Data Science Engineer (Remote – U.S.) at {:companyName} Machine Learning & Data Science Engineer (Remote – U.S.) CyberWinter Studios · United States (Remote) Easy Apply Save Save Machine Learning & Data Science Engineer (Remote – U.S.) at {:companyName} Show more options Get personalized tips to stand out to hirers Practice mock interviews personalized to every role and get custom feedback Try Premium for PKR0 Meet the hiring team Michael Butler 3rd+ Director Of Engineering at CyberWinter Studios Job poster Message About the job CyberWinter Studios is a U.S.-based Defense/Military R&D shop focused on data automation, AI-driven analytics, and defense-sector technology. We build the tools that help mission owners make smarter, faster decisions. We’re looking for a Machine Learning & Data Science Engineer who loves turning complex, scattered, real-world data into high-impact models. We need someone to build ML pipelines end-to-end, from exploration and feature engineering all the way through deployment and monitoring.What You’ll Do Build, train, and deploy machine learning models such as classification, regression, NLP, and more. Develop data pipelines and scalable training workflows. Transition models into production environments. Collaborate with our team to connect your models to real applications and mission workflows. Analyze large datasets, create features, and validate model performance. Help ensure data quality, model reproducibility, and overall system performance. Work closely with developers, SMEs, and mission partners. What You Bring Strong background in data science and machine learning. Proficient in Python (Pandas, NumPy, Scikit-learn; bonus points for PyTorch/TensorFlow). Experience transforming models from prototype to production. Familiar with data engineering concepts like ETL, data integration, and pipeline design. Able to handle large, complex datasets. Possesses strong problem-solving skills and can clearly explain their work to others. U.S.-based and U.S. citizens. Bonus Points Experience with Palantir Foundry (Code Repos, OTS, ML deployment) Background supporting DoD or government data environments Hands-on experience with MLOps tools (MLflow, W&B, Airflow, Ray, etc.)