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Job Description

We are looking for a skilled Generative AI Engineer with a focus on Computer Vision to join our innovative team. The successful candidate will have a robust background in generative AI models, including GANs, VAEs, and transformers, and will leverage these techniques to push the boundaries of computer vision applications. You will work closely with data scientists, software engineers, and product managers to design, implement, and deploy AI-driven applications. Your expertise in machine learning, deep learning, and computer vision will be essential in driving the success of our AI initiatives. 


Responsibilities 


  • Design, develop, and optimize generative AI models such as GANs, VAEs, and transformers for computer vision tasks.
  • Implement state-of-the-art machine learning algorithms to solve complex problems. 
  • Stay abreast of the latest research and advancements in generative AI and machine learning. 
  • Experiment with new techniques and approaches to improve model performance and capabilities. 
  • Collect, preprocess, and manage large datasets for training and evaluation of generative models. 
  • Collaborate with engineering teams to integrate AI models into production systems. 
  • Develop scalable and efficient deployment pipelines for real-time and batch processing. 
  • Monitor the performance of deployed models and implement improvements as needed. 
  • Conduct evaluations to ensure models meet business and technical requirements specifically for NLP and LLM 
  • Work closely with cross-functional teams to understand business requirements and translate them into technical solutions. 
  • Communicate findings, progress, and results to stakeholders through reports and presentations. 

Requirements


  • Bachelor's or master's degree in computer science, Data Science, or a related field. 
  • 5+ years of experience in machine learning, with a focus on generative models and techniques. 
  • Good in Object Oriented Programming and SQL 
  • Experience of developing Machine Learning Models. 
  • Good knowledge of end to end Machine learning lifecycle. 
  • Hands on experience in Python scientific computing eco-system (pandas, numpy, scikit-learn and matplotlib etc)   
  • Strong understanding of natural language processing (NLP), Computer Vision(CV) and machine learning (ML) concepts and ML lifecycle. 
  • Hands-on experience on AI modelling strategies including Fine tuning LLMs, RAG, prompt engineering etc.  
  • Proficiency in programming languages such as Python, R. 
  • Experience of working with modern LLM based libraries/Framework such as LangChain, autogen etc. 
  • Hands on experience of continuously monitoring and evaluating the performance of machine learning models and adjust as needed 
  • Experience of working with cloud services (e.g., AWS, Azure, Google Cloud) and API integration. 
  • Excellent problem-solving skills and the ability to think critically and creatively. 
  • good communication and interpersonal skills, with the ability to work effectively in a team environment. 
  • Experience in leading or mentoring AI Engineers.
  • Excellent communication and collaboration skills
  • Experience of technically leading the team to deliver AI Solutions.

We have an amazing team of 700+ individuals working on highly innovative enterprise projects & products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast-growth fintech, and multiple Silicon Valley startups.


What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015, 27001:2013 & 20000-1:2018 certified. We have a vibrant culture of learning via collaboration and making the workplace fun.


People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves. 


To know more about Confiz Limited, visit: https://www.linkedin.com/company/confiz-pakistan/



Job Details

Job Location
Lahore Pakistan
Company Industry
Other Business Support Services
Company Type
Unspecified
Employment Type
Unspecified
Monthly Salary Range
Unspecified
Number of Vacancies
Unspecified

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