Senior Data Scientist / Machine Learning Engineer
Astro Sirens is an IT staffing agency based in Austin, Texas. We connect talented professionals from around the world with U.S. companies, offering exciting opportunities to work on innovative projects for top clients.
We are currently seeking a Senior Data Scientist / Machine Learning Engineer to help our clients design, build, and deploy scalable machine learning solutions that drive business value. This is a remote position, and we strongly encourage and give preference to candidateswho are eager to collaborate with U.S.-based teams.
Responsibilities
- Design, develop, and deploy machine learning models for real-world production use cases
- Analyze large and complex datasets to extract insights that inform model development and optimization
- Build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment
- Collaborate with data engineers, software engineers, product managers, and business stakeholders to define machine learning requirements
- Implement model monitoring, performance tracking, and retraining strategies
- Optimize models for scalability, performance, and reliability in cloud-based environments
- Ensure data quality, reproducibility, and adherence to best practices in ML development
- Translate machine learning outcomes into clear, actionable insights for technical and non-technical audiences
- Contribute to improving ML standards, tools, and best practices across teams
- Mentor junior data scientists and machine learning engineers
- Bachelor’s or Master’s degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field
- 5+ years of experience in data science, machine learning, or applied AI roles
- Strong proficiency in Python for data processing and machine learning
- Hands-on experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost)
- Strong understanding of supervised and unsupervised learning, deep learning, and model evaluation techniques
- Expertise in SQL and experience with relational databases (PostgreSQL, MySQL, MS SQL)
- Experience deploying machine learning models into production environments
- Familiarity with MLOps practices (model versioning, CI/CD, monitoring, retraining)
- Experience with cloud platforms such as AWS, GCP, or Azure
- Understanding of data governance, model ethics, and data privacy considerations
- Strong communication skills with the ability to work effectively with U.S.-based stakeholders
Preferred Qualifications
- Experience with big data technologies (Spark, Hadoop, or similar)
- Knowledge of Docker, Kubernetes, and containerized ML workflows
- Experience supporting ML systems at scale
- Paid Time Off (PTO)
- Work From Home
- Professional development opportunities
- Training & Development Programs
- Collaborative and inclusive company culture
- Competitive salary and performance-based bonuses
Average salary estimate
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