Sr. Machine Learning Engineer
Yerevan, EMEA-Armenia-Yerevan
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- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
Full-time — employment source
Employment type Full Time
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What you’ll work on
Full postingDesign and develop deep learning models for different data sources (e.g.
Collaborate with the development team on architecture design of proposed solutions and support integration of the model into the production pipeline
Document and transfer technology to product groups across the company
From the employer’s posting
Apply machine learning approaches leading to improvements in orthodontic treatment planning Design and develop deep learning models for different data sources (e.g. 3D meshes, free-form text, table data etc.) Validate and analyse models performance
Validate and analyse models performance Collaborate with the development team on architecture design of proposed solutions and support integration of the model into the production pipeline Document and transfer technology to product groups across the company
Collaborate with the development team on architecture design of proposed solutions and support integration of the model into the production pipeline Document and transfer technology to product groups across the company Ownership of a particular ML component, its maintenance, and improvements
Tools in this posting
- SQL
- Python
- AWS
- Docker
- Kubernetes
- PyTorch
Source — Tool mentions in context
- Experience in ML Ops stack (e.g. Kubernetes, AWS cloud) - Knowledge of SQL Employment type
You will work with following technological stack: - Python - PyTorch
- Solid understanding of deep learning approaches, their limitations and powers (e.g. for semantic/instance segmentation tasks, Visual Transformers, modern LLMs, fusions of different data types, etc.) - Proficiency in the standard technological stack: Python, git, Linux, Docker - Mathematical background for solving ML tasks (optimization methods, Bayesian framework, linear algebra, analytic geometry)
- Experience in С++ is a plus - Experience in ML Ops stack (e.g. Kubernetes, AWS cloud) - Knowledge of SQL
- PyTorch - Docker - Amazon Cloud
- Python - PyTorch - Docker
- Mathematical background for solving ML tasks (optimization methods, Bayesian framework, linear algebra, analytic geometry) - Strong experience in ML frameworks (preferably PyTorch) - Experience in digging through the latest scientific papers and identifying applicability for a particular problem
Job description
Key Responsibilities
- Decompose initial (poorly) stated business requests into separate technical problems and identify a specific ML toolset for a particular problem
- Apply machine learning approaches leading to improvements in orthodontic treatment planning
- Design and develop deep learning models for different data sources (e.g. 3D meshes, free-form text, table data etc.)
- Validate and analyse models performance
- Collaborate with the development team on architecture design of proposed solutions and support integration of the model into the production pipeline
- Document and transfer technology to product groups across the company
- Ownership of a particular ML component, its maintenance, and improvements
- Python
- PyTorch
- Docker
- Amazon Cloud
- Git/Bitbucket
Skills, Knowledge & Expertise
- Master's degree or higher in Computer Science, Statistics, Machine Learning, Statistical Data Modelling or related fields
- 8+ years of experience in deep learning applications for commercial projects (preferably in computer vision tasks)
- Solid understanding of deep learning approaches, their limitations and powers (e.g. for semantic/instance segmentation tasks, Visual Transformers, modern LLMs, fusions of different data types, etc.)
- Proficiency in the standard technological stack: Python, git, Linux, Docker
- Mathematical background for solving ML tasks (optimization methods, Bayesian framework, linear algebra, analytic geometry)
- Strong experience in ML frameworks (preferably PyTorch)
- Experience in digging through the latest scientific papers and identifying applicability for a particular problem
- Strong interpersonal, oral, written, and visual communication skills, with ability to present findings concisely and effectively
- English B2 or higher
- Experience in 3D ML problems is a huge plus (e.g., pose estimation, scene reconstruction, surface/volume segmentation, etc.)
- Hands-on experience with in-depth exploration and customization of LLMs, including fine-tuning, embedding generation and optimization, retrieval-augmented generation (RAG) system development, and model evaluation, is a strong plus
- Scientific publications
- Experience in С++ is a plus
- Experience in ML Ops stack (e.g. Kubernetes, AWS cloud)
- Knowledge of SQL
Employment type
Full Time
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- Pay
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- Location & working pattern
Yerevan, EMEA-Armenia-Yerevan
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- Status in our records
- Unknown — awaiting fresh evidence
- First seen by us
- Aug 31, 2026
- Recorded sightings
- 7
- Last seen by us
- Sep 8, 2026
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