Machine Learning Solutions Architect
3 tygodni temu
Sigma Software is a leading provider of cutting-edge technology solutions, committed to excellence and innovation in the field of Big Data development.
Job DescriptionWe are seeking an experienced Machine Learning Solutions Architect to join our Big Data Competence Center. As a key member of our team, you will be responsible for designing and implementing scalable and cost-effective machine learning solutions for our clients.
Estimated SalaryThe estimated salary for this position is between $120,000 - $180,000 per annum, depending on experience and qualifications.
Key Responsibilities- Collaborate with cross-functional data teams to address diverse, data-centric tasks
- Establish and maintain effective communication with clients and their teams, ensuring alignment on project objectives
- Take ownership of delivering key solution features, from design to deployment
- Engage in requirements gathering and analysis, proposing optimal machine learning strategies and leading the implementation process
- Contribute to pre-sales activities, providing expert input on machine learning and AI solutions
- Develop and implement core system modules, designing scalable and cost-effective solutions
- Conduct code reviews and write comprehensive unit and integration tests to ensure code quality
- Scale distributed systems and infrastructure to support evolving business needs
- Advanced Python and SQL knowledge and expertise
- Experience in model implementation and tuning using popular Machine Learning frameworks like PyTorch, Keras, TensorFlow
- Ability to understand Machine Learning development and deployment processes
- Solid experience with Machine Learning cloud services like AWS SageMaker or Vertex AI and their supplemental features (like SageMaker Pipelines)
- Proficiency in programming for Computer Vision applications and solutions
- Expertise in MLOps, focusing on streamlining and automating ML workflows
- Ability to create and adjust Machine Learning pipelines for the end-to-end Machine Learning development cycle
- Experience in working with Deep Learning models for signal and speech processing, as well as for Natural Language Processing domain
- Proficiency in setting up multi-GPU infrastructure for model training
- Solid understanding in DevOps practices and principles
- Work experience in building and deploying AI solutions
- Familiarity with statistical and data mining techniques and ability to use them when it is appropriate
- Experience in working with Data Analytics
- At least an Upper-Intermediate level of English
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