Middle Machine Learning Engineer
About this role
Developing and optimizing machine learning models for document classification, segmentation, and field extraction forms the core of daily operations. Engineers build scalable data processing systems capable of handling massive PDF documents up to 2,000 pages while designing end-to-end document intelligence pipelines on AWS.
Exadel seeks a Middle Machine Learning Engineer to support an enterprise client in the vehicle lifecycle solutions industry. The engineering team focuses on advanced artificial intelligence and transportation technologies that connect hundreds of insurance companies and repair facilities globally.
Success in the role requires strong technical ownership from initial research through production deployment and monitoring. Engineers who thrive here enjoy collaborating with subject matter experts and communicating complex technical solutions within an asynchronous environment.
What you will do
- Design and implement end-to-end document intelligence pipelines using Amazon Web Services.
- Develop and optimize machine learning models specifically for document classification, segmentation, and field extraction.
- Build scalable data processing systems capable of handling large PDF files containing up to 2,000 pages.
- Collaborate directly with subject matter experts to create and refine precise extraction requirements.
- Take full ownership of features from early research through production deployment and ongoing monitoring.
- Establish rigorous evaluation frameworks and quality metrics to measure and improve extraction accuracy.
What you need
- Demonstrated professional experience programming in Python using libraries such as Pandas, Scikit-Learn, TensorFlow, PyTorch, PyStats, and Pydantic.
- Practical background utilizing AWS tools for machine learning engineering and deployment including SageMaker, Lambda, CloudFormation or CDK, and Step Functions.
- Advanced working knowledge of SQL and data modeling principles.
- Hands-on experience with generative AI for document intelligence, including prompt engineering, retrieval-augmented generation, multi-modal models, and AWS Bedrock or Azure OpenAI APIs.
- Proven experience in experiment design covering power analysis and hypothesis testing.
- Upper-intermediate English proficiency combined with clear written and verbal communication skills suited for remote work.
- Demonstrated capacity to own features from concept to production through proposal, discussion, and execution.
Nice to have
- Experience with document processing tools such as AWS Textract, Azure Document Intelligence, or similar OCR and layout detection systems
- Experience with PDF and image processing libraries like PyMuPDF, OpenCV, and Pillow
- Experience in machine learning and data science including algorithm selection, feature engineering, model training, and hyperparameter tuning
- Experience working with AWS big data technologies including Redshift, S3, EMR, and Glue
Benefits
- International projects
- In-office, hybrid, or remote flexibility
- Medical healthcare
- Recognition program and ongoing learning reimbursement
- Well-being program, team events, and sports compensation
- Referral bonuses and top-tier equipment provision
Skills and tech stack
Questions candidates ask
What is the remote work policy?
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.
When is compensation discussed?
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 tools and technologies will I use?
The tech stack includes Python, AWS tools for machine learning deployment such as SageMaker and Lambda, SQL, and generative AI tools like AWS Bedrock or Azure OpenAI APIs.
What benefits are provided?
Benefits vary by location and contract type, and your recruiter will fill you in on the details. Available offerings include medical healthcare, sports compensation, ongoing learning reimbursement, and top-tier equipment provision.