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Job Description

Company Description

Established in 1986, Sutherland is a global provider of business process and technology management services offering an integrated portfolio of analytics-driven back-office and customer facing solutions that support the entire customer lifecycle.


As a process transformation company, Sutherland rethinks and rebuilds processes for the digital age by combining the speed and insight of design thinking with the scale and accuracy of data analytics. We have been helping customers across industries from financial services to healthcare, achieve greater agility through transformed and automated customer experiences for over 30+ years.


Headquartered in Rochester, N.Y., Sutherland employs thousands of professionals spanning 19 countries around the world. To learn more, please visit us at www.sutherlandglobal.com



Job Description

We are seeking a talented Python Developer with 2 to 4 years of experience who is passionate about machine learning and computer vision. The ideal candidate will have hands-on experience in setting up machine learning models for computer vision applications and training use cases. You will also have experience working with Generative AI models using open-source frameworks like LLaMA, Mistral, and others. This role requires an R&D mindset, with a focus on exploring new technologies and delivering innovative solutions for real-world use cases.


Technical Skills:


  • 2 to 4 years of hands-on experience in Python development, with a focus on machine learning and computer vision applications.
  • Proven experience in setting up and training machine learning models for computer vision use cases.
  • Experience working with Generative AI using open-source models like LLaMA, Mistral, or similar frameworks.
  • Strong knowledge of machine learning frameworks such as TensorFlow, PyTorch, or Keras.
  • Solid understanding of data preprocessing, model evaluation, and optimization techniques.
  • Experience with R&D in AI/ML, exploring new tools and methodologies to solve complex problems.
  • Ability to work independently, with a passion for learning new technologies and applying them to practical use cases.
  • Strong problem-solving skills and the ability to adapt to rapidly evolving project requirements.

Key Responsibilities:


  • Develop, implement, and maintain machine learning models, particularly for computer vision use cases, ensuring high accuracy and performance.
  • Work on Generative AI use cases by leveraging open-source models such as LLaMA, Mistral, and similar frameworks to develop new solutions.
  • Train, fine-tune, and optimize machine learning models based on real-world datasets and use case requirements.
  • Collaborate with cross-functional teams to understand business needs and translate them into technical solutions using AI/ML models.
  • Conduct research and development (R&D) on emerging AI technologies and tools to identify innovative approaches to new and existing use cases.
  • Develop and maintain scripts, tools, and workflows for data preprocessing, model training, evaluation, and deployment.
  • Stay current with the latest trends and advancements in machine learning, computer vision, and Generative AI technologies, applying these insights to projects.
  • Troubleshoot and resolve issues related to model performance, data quality, and deployment pipelines.
  • Document code, processes, and technical decisions to ensure knowledge sharing within the team.

Qualifications
  • Experience with natural language processing (NLP) models and frameworks.
  • Familiarity with cloud platforms like AWS, Azure, or Google Cloud for deploying AI/ML models.
  • Knowledge of containerization technologies like Docker for scalable AI deployments.
  • Experience with version control systems (e.g., Git) and collaboration in Agile environments.

Education:


Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field (or equivalent experience).



Additional Information

All your information will be kept confidential according to EEO guidelines.




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