AI/ML Engineer

NexgenLink (formerly Astro Sirens) is seeking a highly skilled AI/ML Engineer to design, develop, and deploy machine learning and artificial intelligence solutions that drive product innovation and business impact. This role will work closely with engineering, data, product, and business teams to build scalable models, production-grade ML systems, and intelligent applications that solve real-world problems.

The ideal candidate brings a strong foundation in machine learning, software engineering, data pipelines, and cloud-based deployment. This position is well suited for an engineer who is comfortable working across the full machine learning lifecycle, from data preparation and feature engineering to model training, deployment, monitoring, and continuous improvement. The successful candidate will combine strong technical depth with practical problem-solving skills and the ability to collaborate effectively with both technical and non-technical stakeholders in a remote environment aligned with U.S. time zones.

• 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

• 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