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About this role
About the team:
AI Platforms builds the shared AI foundation for Plata, helping product and business teams launch AI solutions faster. We create reusable platforms and tools used across customer care, operations, compliance, telesales, and more.
We work with AWS, Go, Python, and cloud models, combining off-the-shelf solutions with custom infrastructure — including copilots, agents, RAG, voice/OCR services, AI gateway, and ML pipelines.
AI Platforms builds the shared AI foundation for Plata, helping product and business teams launch AI solutions faster. We create reusable platforms and tools used across customer care, operations, compliance, telesales, and more.
We work with AWS, Go, Python, and cloud models, combining off-the-shelf solutions with custom infrastructure — including copilots, agents, RAG, voice/OCR services, AI gateway, and ML pipelines.
About the role:
We’re looking for a Middle+/Senior Applied ML Engineer to build and optimize ML solutions for real business use cases. You’ll work on OCR, ASR, LLMs, and classification tasks — focusing on training, fine-tuning, data quality, and production readiness.
We’re looking for a Middle+/Senior Applied ML Engineer to build and optimize ML solutions for real business use cases. You’ll work on OCR, ASR, LLMs, and classification tasks — focusing on training, fine-tuning, data quality, and production readiness.
Challenges that await you:
- Train, fine-tune, and adapt models for practical internal use cases
- Work on ASR-related tasks, including model training, improvement, and practical adaptation to product needs
- Work with datasets end to end: define data requirements, prepare and structure data, support labeling workflows, and improve data quality
- Optimize models for practical use, including performance, efficiency, and quality trade-offs
- Collaborate with engineers to bring trained or adapted models into real production use cases
What makes you a great fit:
- Demonstrated experience in deep learning and transformers models
- Proficiency in frameworks like PyTorch
- Understanding of how model quality depends on dataset design, labeling quality, and data preparation
- Ability to go deeper than standard training notebooks and make informed decisions during training and optimization
- Strong foundation in data structures, algorithms, and software engineering principles
- Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
- Excellent problem-solving and analytical skills, with a proactive approach to challenges
- Ability to work collaboratively with cross-functional teams
- Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
- Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done
- Experience with content understanding or abuse prevention with LLMs is a plus
Our ways of working:
- Innovative Spirit: A commitment to creativity and groundbreaking solutions
- Honest Feedback: valuing open, transparent communication
- Supportive Team: a strong, collaborative community
- Celebrating Achievements: recognizing our wins together
- High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances
Our benefits:
- Relocation support to one of our hubs — Cyprus, Serbia, or Kazakhstan — with assistance for the employee and their family
- Flexible work from one of our offices or remote
- Healthcare Coverage
- Education Budget: Language lessons, professional training and certifications
- Wellness Budget: Mental health and fitness activity reimbursements
- Vacation policy: 20 days of annual leave and paid sick leave
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