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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer (Python or R) - **Company:** ATC - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Airflow, Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Computer Programming, Continuous Integration, Data Cleansing, Monitoring of Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Tensorflow, Standard Sql, Software Deployment, Software Engineering, Unstructured Data, Google Cloud, Feature Engineering, Pytorch, Apache Spark, Model Validation, Git, Scikit Learn, Kubernetes, Information Technology, Non-relational Database, Data Management, Machine Learning Operations, Software Library, Docker, Unsupervised Learning, Databricks - **Published:** July 10, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p3hn4fruqe ## About the Role * Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. * 3+ years of experience in Machine Learning, Data Science, or Software Development. * Strong programming skills in Python or R. * Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, caret, tidymodels, or similar tools. * Solid understanding of supervised and unsupervised learning techniques. * Experience with data preprocessing, feature engineering, and model evaluation. * Knowledge of SQL and working with relational or non-relational databases. * Experience building and deploying ML models in production environments. * Familiarity with Git, Docker, and CI/CD workflows. * Strong analytical, problem-solving, and communication skills. Preferred Qualifications * Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. * Familiarity with MLOps tools such as MLflow, Kubeflow, Airflow, or SageMaker. * Experience with model monitoring, drift detection, and retraining strategies. * Knowledge of NLP, computer vision, time series forecasting, or recommendation systems. * Experience working in Agile or cross-functional product teams. * Exposure to big data tools such as Spark or Databricks. ## Description We are looking for a Machine Learning Engineer with 3+ years of experience in building, training, and deploying machine learning models. The ideal candidate will have strong programming skills in Python or R and hands-on experience working with data, model development, evaluation, and production deployment. You will collaborate with data scientists, software engineers, and business stakeholders to design scalable ML solutions that solve real-world problems., * Develop, train, and deploy machine learning models using Python or R. * Work with structured and unstructured data to build predictive and analytical solutions. * Perform data preprocessing, feature engineering, model selection, and hyperparameter tuning. * Evaluate model performance using appropriate metrics and validation techniques. * Build and maintain ML pipelines for training, testing, and inference. * Collaborate with data engineers and software teams to integrate models into applications and workflows. * Develop APIs or services to expose machine learning models for production use. * Monitor model performance in production and retrain models as needed. * Analyze business requirements and translate them into machine learning solutions. * Document model design, experiments, and deployment processes. * Troubleshoot, optimize, and maintain ML systems in production environments. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [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) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)