AI/ML Engineer
Astro Sirens LLC
contract
Posted on:
Location Type: Remote
Location: Philippines
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Tech Stack
About the role
- Design, develop, and deploy machine learning and artificial intelligence solutions that drive product innovation and business impact
- Work closely with engineering, data, product, and business teams to build scalable models, production-grade ML systems, and intelligent applications
- Handle the full machine learning lifecycle, from data preparation and feature engineering to model training, deployment, monitoring, and continuous improvement
- Combine strong technical depth with practical problem-solving skills and collaborate effectively with both technical and non-technical stakeholders in a remote environment aligned with U.S. time zones
Requirements
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, or a related quantitative field
- Minimum 5 years of professional experience in machine learning, artificial intelligence, or software engineering roles with a strong machine learning focus
- Strong proficiency in Python and hands-on experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy
- Proven experience building, evaluating, deploying, and supporting machine learning models in production environments
- Strong understanding of supervised and unsupervised learning, feature engineering, model evaluation, and statistical analysis
- Experience designing and maintaining data pipelines and machine learning workflows in cloud environments such as AWS, Microsoft Azure, or Google Cloud Platform
- Familiarity with APIs, microservices, and backend engineering concepts for integrating machine learning solutions into production systems
- Strong SQL skills and experience working with large-scale structured and unstructured datasets
- Strong written and verbal communication skills in English, with the ability to explain complex technical concepts clearly to technical and non-technical stakeholders
- Demonstrated ability to work effectively in a remote environment while aligned with U.S. time zones
- Preferred experience with MLOps tools and practices such as MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, model monitoring, CI/CD, and lifecycle management
- Preferred experience with natural language processing, computer vision, recommender systems, or time-series forecasting
- Preferred familiarity with distributed processing technologies such as Spark, Hadoop, or Ray
- Preferred experience with vector databases, embeddings, retrieval pipelines, and large language model integrations
- Preferred exposure to generative AI frameworks and tools such as LangChain, LangGraph, Hugging Face, and OpenAI APIs
- Preferred experience building scalable inference services using Docker, Kubernetes, and cloud-native deployment patterns
- Preferred knowledge of data governance, model explainability, responsible AI practices, and model risk management
- Preferred experience working in fast-paced, cross-functional product or platform teams
Benefits
- Competitive compensation
- Flexible remote work aligned with U.S. time zones
- Opportunity to work on innovative AI and machine learning initiatives with meaningful business impact
- Collaborative, technically strong, and forward-looking engineering environment
- Long-term career growth and professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningartificial intelligencePythonscikit-learnTensorFlowPyTorchPandasNumPySQLdata preparation
Soft Skills
problem-solvingcommunicationcollaborationremote workstakeholder engagementtechnical explanationadaptabilityteamworktime managementcross-functional collaboration