Middle Machine Learning Engineer

Exadel
Bulgaria +2 more
Remote

Who this role is best for

Best suited to ML engineers with experience in document intelligence and GenAI working in transportation and insurance domains.

Best fit for

  • Candidates with experience in end-to-end ML pipeline development and deployment on AWS
    — “Design and implement end-to-end document intelligence pipelines on AWS”
  • Professionals with strong communication skills for remote and asynchronous collaboration
    — “Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment”

Things to consider

  • The role requires a high level of autonomy in feature ownership and decision-making
    — “Own features from research through production deployment and monitoring”
  • English proficiency is a non-negotiable requirement for this role
    — “English Level Upper-intermediate”

How to stand out

  • Highlight experience with ML model optimization and production deployment in your resume
    — “Develop and optimize ML models for document classification, segmentation, and field extraction”
  • Showcase your ability to communicate complex technical problems clearly and iteratively
    — “Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions”
  • Emphasize your hands-on experience with AWS ML tools and document intelligence systems
    — “Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)”
  • Demonstrate your skills in building scalable data processing systems for large documents
    — “Build scalable data processing systems handling PDFs up to 2000 pages”
  • Include examples of working with GenAI and RAG in your application materials
    — “Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation)”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designing and implementing end-to-end document intelligence pipelines
  • owning features from research through production deployment
Typical background
data sciencemachine learning

Skills & requirements

Required

Document Intelligence PipelinesML Model DevelopmentAWS Tools

Preferred

Document Processing ToolsPDF And Image Processing Libraries

Stack & domain

PythonPandasScikitlearnTensorFlowPyTorchAWS ToolsSQLGenaiDocument IntelligencePrompt EngineeringRAGMulti-modal ModelsExperiment DesignPower AnalysisHypothesis TestingPDF And Image ProcessingAWS Big Data TechnologiesCommunicationProblem-solvingTeamworkAIDocument ProcessingData Science

About the role

Original posting from Exadel via Greenhouse

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

Experience in 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: Exadel careers (Greenhouse)

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