Remote Machine Learning Engineer - Big Data Analytics
Summary
Fully remote machine learning engineer for a data analytics firm, owning the end-to-end ML lifecycle — building data pipelines, training and deploying models on big data tech like Spark/Hadoop — using Python/Scala, cloud ML services, and MLOps practices.
About the Role
Our client, a fast-growing data analytics firm, is seeking a Remote Machine Learning Engineer with expertise in big data to join their globally distributed team. This fully remote position is ideal for an individual passionate about building and deploying scalable machine learning models that derive actionable insights from massive datasets. You will be responsible for the end-to-end ML lifecycle, from data ingestion and feature engineering to model training, evaluation, and deployment. This role offers the flexibility to work from anywhere while collaborating with a talented team on challenging projects that impact key business decisions. We are looking for a proactive and detail-oriented engineer who can leverage big data technologies and advanced ML techniques to drive innovation in data-driven solutions. This is a fully remote opportunity focused on collaborative development and asynchronous workflows.
Key Responsibilities
- Develop, train, and deploy machine learning models using large-scale datasets.
- Design and implement robust data pipelines for ML model training and inference.
- Utilize big data technologies (e.g., Spark, Hadoop) for data processing and feature engineering.
- Implement MLOps best practices for model versioning, monitoring, and deployment.
- Collaborate with data scientists and software engineers to integrate ML models into production systems.
- Optimize ML algorithms and data processing tasks for performance and scalability.
- Evaluate model performance and identify opportunities for improvement.
- Stay updated on the latest advancements in machine learning and big data technologies.
- Document ML models, pipelines, and deployment processes.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
- 3+ years of professional experience as a Machine Learning Engineer or Data Scientist with a strong engineering focus.
- Proven experience working with big data technologies such as Apache Spark, Hadoop, or similar distributed computing frameworks.
- Proficiency in programming languages like Python or Scala, and ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
- Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
- Solid understanding of ML algorithms, model evaluation techniques, and feature engineering.
- Familiarity with MLOps tools and CI/CD practices for ML.
- Strong analytical and problem-solving skills.
- Excellent communication skills, capable of working effectively in a remote setting.
- Demonstrated ability to manage multiple tasks and work independently.
Benefits
- Competitive salary and performance bonuses.
- Fully remote work arrangement with flexible hours.
- Home office stipend for setting up a productive workspace.
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and company holidays.
- Opportunities for professional development, including online courses and conferences.
- Access to cutting-edge tools and technologies.
- Virtual team events to foster connection and collaboration.