Middle Machine Learning Engineer

Exadel
Bulgaria +2 more
RemoteCareer-pivot friendly

Who this role is best for

Strong fit for candidates who design and own end-to-end ML pipelines and have experience with GenAI for document intelligence, working in a remote and asynchronous environment with a focus on scalable data systems.

Best fit for

  • Candidates with experience in deploying GenAI for document intelligence and a track record of full-cycle feature ownership
    — “Own features from research through production deployment and monitoring”
  • Individuals who have built scalable data processing systems handling large PDFs and have ML deployment expertise on AWS
    — “Build scalable data processing systems handling PDFs up to 2000 pages”
  • Professionals skilled in Python-based ML frameworks and AWS ML tools who can collaborate effectively with subject matter experts
    — “Collaborate with subject matter experts to create and refine requirements for extraction”

Things to consider

  • English proficiency at upper-intermediate level is a key requirement for this remote role
    — “English Level Upper-intermediate”
  • The role demands a high level of communication ability for asynchronous collaboration
    — “Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment”

How to stand out

  • Demonstrate familiarity with GenAI techniques and production deployment using AWS Bedrock or Azure OpenAI APIs
    — “Experience with GenAI for document intelligence, including prompt engineering, RAG, multi-modal models, and production deployment using AWS Bedrock or Azure OpenAI APIs”
  • Emphasize your experience with Python libraries like Pandas, ScikitLearn, and Pydantic in your application materials
    — “Experience in Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)”
  • Include examples of how you've established evaluation frameworks and quality metrics for ML models
    — “Establish evaluation frameworks and quality metrics for extraction accuracy”
Pace · Fast PacedCollaboration · MediumAutonomy · MediumDecision Impact · Team

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

What success looks like

  • Document intelligence pipelines
  • ML model optimization
  • data processing systems
Typical background
Computer ScienceData ScienceMachine Learning

Skills & requirements

Required

Document IntelligenceML Model DevelopmentData ProcessingAWS ToolsSQLPythonExperiment Design

Preferred

GenaiDocument Processing ToolsPDF And Image ProcessingBig Data Technologies

Stack & domain

PythonPandasScikitlearnTensorFlowPyTorchPystatsPydanticAWS Tools For ML Engineering And ML DeploymentSQLData ModelingGenai For Document IntelligencePrompt EngineeringRAGMulti-modal ModelsExperiment DesignPower AnalysisHypothesis TestingAWS Big Data TechnologiesCommunicationTeamworkCollaborationProblem-solvingLeadershipInnovationFlexibilityUrgencyTechnical Problem-solvingMachine LearningData ScienceDocument IntelligenceAWSBig DataAIGenai

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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