Team Lead – AI/ML
Devsinc
AWSAzureCloudGoogle Cloud PlatformHadoopPythonPyTorchScikit-LearnSparkTensorflow
AI Engineer
Domyn
full-time
Posted on:
Location Type: Hybrid
Location: Madrid • 🇪🇸 Spain
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudGoogle Cloud PlatformPythonPyTorchTensorflow
About the role
- Join Domyn's team in Madrid to implement and scale large language models and generative AI systems
- Bridge the gap between cutting-edge research and practical applications, turning AI concepts into production-ready systems
- Report to the Finance Product Development Lead
- Work closely with the research team and data engineers to build and optimize AI solutions
- Implement and optimize large language models and generative AI systems for production environments
- Collaborate with researchers and clients to translate research prototypes into scalable, efficient implementations tailored to client needs
- Design and develop AI infrastructure components for model training, fine-tuning, and inference
- Optimize AI models for performance, latency, and resource utilization
- Implement systems for model evaluation, monitoring, and continuous improvement
- Develop APIs and integration points for AI services within the product ecosystem
- Troubleshoot complex issues in AI systems and implement solutions
- Contribute to the development of internal tools and frameworks for AI development
- Stay current with emerging techniques in AI engineering and LLM deployment
- Collaborate with data engineers to ensure proper data flow for AI systems
- Implement safety measures, content filtering, and responsible AI practices
Requirements
- 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 (nice-to-have)
- Knowledge of distributed computing and large-scale model training (nice-to-have)
- Familiarity with model optimization techniques (quantization, pruning, distillation) (nice-to-have)
- Experience with real-time inference systems and low-latency Al services (nice-to-have)
- Understanding of Al ethics, bias mitigation, and responsible Al development (nice-to-have)
- Experience with model serving platforms (TorchServe, TensorFlow Serving, Triton) (nice-to-have)
- Knowledge of vector databases and similarity search for LLM applications (nice-to-have)
- Experience with reinforcement learning and RLHF techniques (nice-to-have)
- Familiarity with front-end technologies for Al application interfaces (nice-to-have)
Benefits
- Competitive compensation (base salary)
- Performance-based bonuses
- Additional compensation components based on experience
- Comprehensive benefits as part of the total compensation package
ATS Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learninglarge language modelsgenerative AIPythonPyTorchTensorFlowmodel optimizationfine-tuningprompt engineeringreal-time inference
Soft skills
communicationproblem-solvingattention to detailcollaborationinterfacing with clients
Certifications
Bachelor's degree in Computer ScienceMaster's degree in Engineering
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