Middle Machine Learning Engineer
About this role
Complex document processing challenges require robust engineering solutions to extract structured insights from unstructured PDFs spanning thousands of pages. Exadel seeks a Middle Machine Learning Engineer to join a client project supporting a leading provider of vehicle lifecycle solutions. The engineering team builds advanced document intelligence pipelines and scalable data systems that power transportation and insurance networks.
Daily responsibilities involve designing end-to-end extraction workflows on AWS, optimizing models for document classification, and deploying generative AI capabilities into production. The person who succeeds in this role combines strong technical proficiency in Python and AWS with clear asynchronous communication skills, enabling them to own features from initial concept through monitoring.
What you will do
- Design and implement end-to-end document intelligence pipelines on AWS.
- Develop and optimize machine learning models for document classification, segmentation, and field extraction.
- Build scalable data processing systems capable of handling large PDF documents.
- Collaborate with subject matter experts to create and refine requirements for extraction.
- Own features through the entire lifecycle from research to production deployment and monitoring.
- Establish evaluation frameworks and quality metrics to measure extraction accuracy.
What you need
- Demonstrate experience using Python including Pandas, Scikit-Learn, TensorFlow or PyTorch, and Pydantic.
- Bring hands-on experience with AWS tools for machine learning engineering and deployment such as Sagemaker, Lambda, CloudFormation, and Step Functions.
- Possess advanced knowledge of SQL and data modeling.
- Have experience with generative AI for document intelligence including prompt engineering, RAG, multi-modal models, and AWS Bedrock or Azure OpenAI APIs.
- Show background in experiment design such as power analysis and hypothesis testing.
- Maintain upper-intermediate English proficiency with strong written and verbal communication skills suitable for a remote and asynchronous work environment.
- Demonstrate the capacity to communicate complex technical problems clearly and propose iterative solutions.
Nice to have
- Experience with document processing tools like AWS Textract or Azure Document Intelligence
- Experience with PDF and image processing libraries such as PyMuPDF, OpenCV, or Pillow
- Background in general machine learning and data science including algorithm selection and feature engineering
- Experience working with AWS big data technologies like Redshift, S3, EMR, and Glue
Benefits
- International projects
- In-office, hybrid, or remote flexibility
- Medical healthcare
- Recognition program
- Ongoing learning & reimbursement
- Well-being program
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
The role offers in-office, hybrid, or remote flexibility. Proficiency in both written and verbal communication is required for a remote and largely asynchronous work environment.
What compensation details are available?
Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place.
What technologies will I work with on this project?
The tech stack includes Python, Pandas, Scikit-Learn, TensorFlow or PyTorch, SQL, and various AWS tools for machine learning engineering and deployment. You will also work with generative AI for document intelligence including prompt engineering, RAG, and AWS Bedrock or Azure OpenAI APIs.
What benefits are included with the role?
Benefits vary by location and contract type, and your recruiter will fill you in on the details. Available offerings include international projects, medical healthcare, a recognition program, ongoing learning reimbursement, a well-being program, and sports compensation.
The application is on the official Exadel Inc (Website) careers page.
Apply on company site