About this role
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.
What You’ll DoDesign, 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. Requirements
What You’ll Bring3–8 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.Benefits
Why AcceptedCompetitive 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.Your Next StepApply 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.