Machine Learning Engineer - Python
First seen by Alion on Oct 10, 2026.
Role Overview:
As a Machine Learning Engineer, you will design and deploy intelligent models that automate document verification and predictive case assessment. You will collaborate closely with data scientists, legal experts, and software engineers to translate complex immigration requirements into scalable algorithmic solutions. Your work will directly impact the speed and accuracy of case processing, significantly reducing manual overhead and improving the overall experience for our global clientele.
Key Responsibilities:
- Architect and implement end-to-end machine learning pipelines to automate document classification and data extraction tasks for immigration filings.
- Develop and fine-tune deep learning models to identify patterns in regulatory changes, ensuring our systems remain compliant with evolving international laws.
- Optimize model performance and latency by deploying solutions on AWS infrastructure to support high-concurrency user traffic.
- Collaborate with cross-functional teams to integrate predictive analytics into our core platform, driving data-informed decision-making for case managers.
- Maintain high standards of code quality and documentation to ensure the long-term scalability and maintainability of our ML ecosystem.
Required Skillset:
- Demonstrated expertise in building and deploying production-grade models using Python, with deep proficiency in libraries such as Scikit-Learn, Pandas, and NumPy.
- Proven ability to design neural networks and complex architectures using Deep Learning frameworks like TensorFlow or PyTorch.
- Strong background in software engineering principles with the ability to write clean, efficient code in Java for backend integration.
- Hands-on experience managing cloud-based ML workflows and model deployment within AWS environments.
- Exceptional analytical and problem-solving skills, with the ability to communicate complex technical concepts to non-technical stakeholders.
- Ability to thrive in a distributed, global work environment, demonstrating self-motivation and the capacity to manage projects independently across different time zones.
- A minimum of 3 to 12 years of professional experience in data science and machine learning roles.
Skills
Deep Learning, Python, Tensorflow, Data Science, Data Scientist, Java, Pandas, Numpy