Senior ML Engineer

Working model: Hybrid | Type: Full-time

Accepted is a software and digital transformation services firm helping clients accelerate innovation in Finance, Energy, Gaming, Telco, and beyond. With 20+ years of engineering excellence, we’re known for building outcome-driven solutions and high-performing teams that feel like part of your own.

We’re looking for a Senior ML Engineer to strengthen our hybrid delivery teams.

• Design, develop and deploy machine learning solutions for document-intensive environments, focusing on intelligent document processing, automation and information extraction;
• Develop and optimize NLP and LLM-based applications for document understanding, including classification, entity recognition, semantic search and retrieval;
• Build and maintain end-to-end ML pipelines, including data preprocessing, training, evaluation, deployment and monitoring;
• Work on document ingestion and processing workflows (PDFs, scanned documents, unstructured data) and enable metadata extraction and indexing;
• Implement and optimize RAG pipelines and LLM integrations for enterprise knowledge systems;
• Collaborate with product, engineering and business teams to translate document management and operational needs into scalable ML solutions;
• Contribute to the design and evolution of internal AI platforms and automation pipelines;
• Ensure performance, scalability and reliability of ML systems in production environments;
• Support experimentation, model tuning and continuous improvement of ML solutions.
  

• 3–8 years of experience in Machine Learning / AI engineering roles, ideally in document-heavy or enterprise environments;
• Strong experience in:
• NLP and document understanding;
• LLMs and prompt engineering;
• Information extraction, classification and semantic search.
• Hands-on experience with Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face);
• Experience with document processing technologies (OCR, intelligent document processing, metadata extraction);
• Experience building and deploying ML pipelines (MLOps, APIs, Docker, cloud environments such as AWS/Azure/GCP);
• Familiarity with vector databases, embeddings and retrieval systems;
• Understanding of data engineering concepts (ETL pipelines, data preprocessing, large-scale text processing);
• Ability to design scalable solutions for high-volume document workflows and enterprise platforms;
• Bachelor’s or Master’s degree from a reputable university in Computer Science, Machine Learning, Data Science or a related field.

• Competitive compensation aligned with your experience and skills;
• Annual bonus scheme linked to company performance;
• Private medical, dental, and life insurance coverage;
• Ongoing professional development through training and certifications;
• Structured mentoring to support your growth and advancement.

Apply today and grow with a company where innovation, trust, and excellence come together. All applications are confidential. We are proud to be an Equal Opportunity Employer.