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Key Responsibilities
- Implement and optimize large language models and generative Al systems for production environments;
- Collaborate with researchers and clients to translate research prototypes into scalable, efficient implementations tailored to client needs;
- Design and develop Al infrastructure components for model training, fine-tuning, and inference;
- Optimize Al models for performance, latency, and resource utilization;
- Implement systems for model evaluation, monitoring, and continuous improvement;
- Develop APls and integration points for Al services within our product ecosystem;
- Troubleshoot complex issues in Al systems and implement solutions;
- Contribute to the development of internal tools and frameworks for Al development;
- Stay current with emerging techniques in Al engineering and LLM deployment;
- Collaborate with data engineers to ensure proper data flow for Al systems;
- Implement safety measures, content filtering, and responsible Al practices
- Bachelor's or Master's degree in Computer Science, Engineering, or related technical field;
- 3+ years of hands-on experience implementing and optimizing machine learning models;
- Strong programming skills in Python and related ML frameworks (PyTorch, TensorFlow);
- Experience with deploying and scaling Al models in production environments;
- Familiarity with large language models, transformer architectures, and generative Al;
- Knowledge of cloud platforms (AWS, GCP, Azure) and containerization technologies;
- Understanding of software engineering best practices (version control, CI/CD, testing);
- Experience with ML engineering tools and platforms (MLflow, Kubeflow, etc.);
- Strong communication skills and experience interfacing with clients or external partners;
- Strong problem-solving skills and attention to detail;
- Ability to collaborate effectively in cross-functional teams
- Experience with fine-tuning and prompt engineering for large language models;
- Knowledge of distributed computing and large-scale model training;
- Familiarity with model optimization techniques (quantization, pruning, distillation);
- Experience with real-time inference systems and low-latency Al services;
- Understanding of Al ethics, bias mitigation, and responsible Al development;
- Experience with model serving platforms (TorchServe, TensorFlow Serving, Triton);
- Knowledge of vector databases and similarity search for LLM applications;
- Experience with reinforcement learning and RLHF techniques;
- Familiarity with front-end technologies for Al application interfaces
Perks
Domyn offers a competitive compensation structure, including salary, performance-based bonuses, and additional components based on experience. All roles include comprehensive benefits as part of the total compensation package.
About Domyn
Domyn is a company specializing in the research and development of Responsible AI for regulated industries, including financial services, government, and heavy industry. It supports enterprises with proprietary, fully governable solutions based on a composable AI architecture — including LLMs, AI agents, and one of the world's largest supercomputers.
At the core of Domyn's product offer is a chip-to-frontend architecture that allows organizations to control the entire AI stack — from hardware to application — ensuring isolation, security, and governance throughout the AI lifecycle.
Its foundational LLMs, Domyn Large and Domyn Small, are designed for advanced reasoning and optimized to understand each business's specific language, logic, and context. Provided under an open-enterprise license, these models can be fully transferred and owned by clients.
Once deployed, they enable customizable agents that operate on proprietary data to solve complex, domain-specific problems. All solutions are managed via a unified platform with native tools for access management, traceability, and security.
Powering it all, Colosseum — a supercomputer in development using NVIDIA Grace Blackwell Superchips — will train next-gen models exceeding 1T parameters.
Domyn partners with Microsoft, NVIDIA, and G42. Clients include Allianz, Intesa Sanpaolo, and Fincantieri.
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Key Skills
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