Time since we first saw it
Day 2
Early. Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Senior Machine Learning Engineer
Bulgaria, Hungary, Poland
Actively hiring, first seen by us 2 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and implement end-to-end document intelligence pipelines on AWS
Develop and optimize ML models for classification, segmentation and field extraction
Build scalable data processing for PDFs up to 2000 pages
Own features from research through production deployment and monitoring
Establish evaluation frameworks and quality metrics for extraction accuracy
From the employer’s posting
Design and implement end-to-end document intelligence pipelines on AWS
Develop and optimize ML models for document classification,segmentation, and field extraction
Build scalable data processing systems handling PDFs up to 2000 pages
Own features from research through production deployment and monitoring
Establish evaluation frameworks and quality metrics for extraction accuracy
What you’ll bring
All qualificationsCore experience
- Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
- Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
- Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems)
- Experience in experiment design (power analysis and hypothesis testing)
- Experience with PDF and Image processing libraries (e.g.
- Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
Qualification wording
Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems)
Experience in experiment design (power analysis and hypothesis testing)
Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
About Exadel
The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 2, 20262 days ago
- Recorded sightings
- 3
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Exadel is hiring
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
- 14% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Redshift
- S3
- SageMaker
- pandas
- PyTorch
- TensorFlow
Where the posting names them
What You Bring - Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic) - Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
- Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions) - Advanced knowledge of SQL and Data Modeling - Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
What You’ll Do - Design and implement end-to-end document intelligence pipelines on AWS - Develop and optimize ML models for document classification,segmentation, and field extraction
- Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic) - Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions) - Advanced knowledge of SQL and Data Modeling
- Advanced knowledge of SQL and Data Modeling - Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs - Experience in experiment design (power analysis and hypothesis testing)
Nice to have - Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems) - Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
- Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks) - Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.) English Level
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
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Already applied? Track this application
Has Exadel posted this job before?
Yes. We’ve followed 3 other Senior Machine Learning Engineer jobs there since June 2026. One came down after 49 days. 2 are still up.
Large employers often post one title for several teams, so these can be separate openings.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Why Join Exadel
We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.
From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.
What powers it all? Our people are ambitious, collaborative, and constantly evolving.
About the Client
The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.
What You’ll Do
- Design and implement end-to-end document intelligence pipelines on AWS
- Develop and optimize ML models for document classification,segmentation, and field extraction
- Build scalable data processing systems handling PDFs up to 2000 pages
- Collaborate with subject matter experts to create and refine requirements for extraction
- Own features from research through production deployment and monitoring
- Establish evaluation frameworks and quality metrics for extraction accuracy
What You Bring
- Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
- Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
- Advanced knowledge of SQL and Data Modeling
- Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
- Experience in experiment design (power analysis and hypothesis testing)
- Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
- Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
- Experience owning a feature from concept to production, including proposal, discussion, and execution
Nice to have
- Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems)
- Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
- Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
- Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)
English Level
Upper-intermediate
Legal & Hiring Information
- Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more.
- Reasonable accommodations are available to enable individuals with disabilities to perform essential functions.
- Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs.
- 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.
Your Benefits at Exadel
Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.
- International projects
- In-office, hybrid, or remote flexibility
- Medical healthcare
- Recognition program
- Ongoing learning & reimbursement
- Well-being program
- Team events & local benefits
- Sports compensation
- Referral bonuses
- Top-tier equipment provision
Exadel Culture
We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bulgaria, Hungary, Poland
- Experience in experiment design (power analysis and hypothesis testing) - Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment - Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
More source context
- International projects - In-office, hybrid, or remote flexibility - Medical healthcare
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.