[Hiring] Senior Machine Learning Engineer @Astro Sirens LLC

Role Description

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 candidates based in India who are eager to collaborate with U.S.-based teams.

• 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

Qualifications

• 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

Benefits

• Paid Time Off (PTO)
• Work From Home
• Professional development opportunities
• Training & Development Programs
• Collaborative and inclusive company culture
• Competitive salary and performance-based bonuses