298 Artificial Intelligence Machine Learning Engineer AI Ml jobs in Pakistan

• Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources
• Collaborate with data scientists to transform machine learning models into production-ready applications
• Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process
• Evaluate and integrate new data management and processing technologies to enhance analytics capabilities
• Create and manage data repositories, following best practices for data governance and security
• Develop documentation and provide training to team members on data systems and workflows
• Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment
• Stay updated on the latest industry trends and technologies in data engineering and machine learning
• Lead the development and deployment of machine learning models that drive key business metrics and outcomes
• Build and maintain scalable data pipelines and feature stores for training and inference use cases
• Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery
• Monitor and retrain models in production to ensure performance over time and handle data drift issues
• Contribute to architectural decisions on data platforms and model-serving infrastructure
• Mentor junior team members and help shape best practices in data science engineering
  
  

• Bachelor's or Master's degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline
• 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions
• Demonstrated experience translating business problems into data science projects with measurable outcomes
• Prior experience working closely with business stakeholders to operationalize models and drive ROI
  
  

• Strong analytical and problem-solving skills with attention to detail
• Excellent communication skills, both verbal and written, to convey technical concepts effectively
• Ability to work collaboratively in a fast-paced team environment and manage multiple priorities
• Motivated self-starter with a passion for learning and applying new technologies

Devsinc is seeking a talented Data Science Engineer who will play a pivotal role in designing, implementing, and optimizing data-driven solutions that enhance our machine learning capabilities. The ideal candidate has a strong background in data engineering combined with machine learning and is passionate about applying modern technologies to drive innovation. You will collaborate with data scientists, analysts, and software engineers to create robust data pipelines and deploy advanced models.

Key Responsibilities:

• Design and implement scalable data pipelines to efficiently collect, process, and analyze large volumes of data from various sources.
• Collaborate with data scientists to transform machine learning models into production-ready applications.
• Optimize and maintain existing data workflows, ensuring data accuracy, quality, and integrity throughout the process.
• Evaluate and integrate new data management and processing technologies to enhance analytics capabilities.
• Create and manage data repositories, following best practices for data governance and security.
• Develop documentation and provide training to team members on data systems and workflows.
• Utilize cloud platforms (e.g., AWS, Azure, Google Cloud) for data storage, processing, and machine learning deployment.
• Stay updated on the latest industry trends and technologies in data engineering and machine learning.
• Lead the development and deployment of machine learning models that drive key business metrics and outcomes.
• Build and maintain scalable data pipelines and feature stores for training and inference use cases.
• Work closely with product, engineering, and business teams to identify high-impact data science opportunities and close the loop on delivery.
• Monitor and retrain models in production to ensure performance over time and handle data drift issues.
• Contribute to architectural decisions on data platforms and model-serving infrastructure.
• Mentor junior team members and help shape best practices in data science engineering.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related technical discipline.
• 3-5 years of professional experience in data science and engineering roles, with a track record of delivering production-ready solutions.
• Demonstrated experience translating business problems into data science projects with measurable outcomes.
• Prior experience working closely with business stakeholders to operationalize models and drive ROI.

Soft Skills:

• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills, both verbal and written, to convey technical concepts effectively.
• Ability to work collaboratively in a fast-paced team environment and manage multiple priorities.
• Motivated self-starter with a passion for learning and applying new technologies.

Devsinc is on the lookout forData Scientists with 6 months - 1.5 years of experience, with a particular focus on machine learning (ML). This role is ideal for individuals who have begun to develop their skills in ML methodologies and are eager to apply this knowledge to solve real-world challenges. The successful candidate will demonstrate a strong foundation in ML techniques, an analytical mindset for unraveling complex data puzzles, and a dedication to contributing to data-driven decisions and innovations.

Responsibilities:

• Design, develop, and deploy machine learning models to address specific business challenges. This includes data preprocessing, feature engineering, model selection, training, and validation.
• Perform exploratory data analysis to uncover hidden patterns, correlations, and insights within structured and unstructured data. Utilize these findings to refine ML models and approaches.
• Engage with a multidisciplinary team of data scientists, engineers, and business stakeholders to refine data requirements and deliver ML-driven solutions.
• Create clear visualizations to represent the outcomes of ML models and analyses. Prepare comprehensive reports and presentations that translate complex ML concepts and findings into actionable business insights.
• Actively pursue learning opportunities in advanced machine learning techniques and algorithms. Incorporate cutting-edge research and tools into projects to enhance model performance and efficiency.
• Assist in the development of prototypes for predictive models and other ML applications, testing their effectiveness in real-world scenarios.
• Cross-Functional Application of Insights, Datasets, Code, and Models: Look for opportunities to use insights/datasets/code/models across other functions in the organization (for example in the HR and marketing departments)
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.

Devsinc is on the lookout forData Scientists with 6 months - 1.5 years of experience, with a particular focus on machine learning (ML). This role is ideal for individuals who have begun to develop their skills in ML methodologies and are eager to apply this knowledge to solve real-world challenges. The successful candidate will demonstrate a strong foundation in ML techniques, an analytical mindset for unraveling complex data puzzles, and a dedication to contributing to data-driven decisions and innovations.

Responsibilities:

• Design, develop, and deploy machine learning models to address specific business challenges. This includes data preprocessing, feature engineering, model selection, training, and validation.
• Perform exploratory data analysis to uncover hidden patterns, correlations, and insights within structured and unstructured data. Utilize these findings to refine ML models and approaches.
• Engage with a multidisciplinary team of data scientists, engineers, and business stakeholders to refine data requirements and deliver ML-driven solutions.
• Create clear visualizations to represent the outcomes of ML models and analyses. Prepare comprehensive reports and presentations that translate complex ML concepts and findings into actionable business insights.
• Actively pursue learning opportunities in advanced machine learning techniques and algorithms. Incorporate cutting-edge research and tools into projects to enhance model performance and efficiency.
• Assist in the development of prototypes for predictive models and other ML applications, testing their effectiveness in real-world scenarios.
• Cross-Functional Application of Insights, Datasets, Code, and Models: Look for opportunities to use insights/datasets/code/models across other functions in the organization (for example in the HR and marketing departments)
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.

Devsinc is on the lookout for Data Scientists with 6 months - 1.5 years of experience, with a particular focus on machine learning (ML). This role is ideal for individuals who have begun to develop their skills in ML methodologies and are eager to apply this knowledge to solve real-world challenges. The successful candidate will demonstrate a strong foundation in ML techniques, an analytical mindset for unraveling complex data puzzles, and a dedication to contributing to data-driven decisions and innovations.

Responsibilities:

• Design, develop, and deploy machine learning models to address specific business challenges. This includes data preprocessing, feature engineering, model selection, training, and validation.
• Perform exploratory data analysis to uncover hidden patterns, correlations, and insights within structured and unstructured data. Utilize these findings to refine ML models and approaches.
• Engage with a multidisciplinary team of data scientists, engineers, and business stakeholders to refine data requirements and deliver ML-driven solutions.
• Create clear visualizations to represent the outcomes of ML models and analyses. Prepare comprehensive reports and presentations that translate complex ML concepts and findings into actionable business insights.
• Actively pursue learning opportunities in advanced machine learning techniques and algorithms. Incorporate cutting-edge research and tools into projects to enhance model performance and efficiency.
• Assist in the development of prototypes for predictive models and other ML applications, testing their effectiveness in real-world scenarios.
• Cross-Functional Application of Insights, Datasets, Code, and Models: Look for opportunities to use insights/datasets/code/models across other functions in the organization (for example in the HR and marketing departments).
• Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
• Maintain clear and coherent communication, both verbal and written, to understand data needs and report results.

• Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field with significant coursework or projects in machine learning.
• A minimum of 6 months - 1.5 years of experience in machine learning or data science, with a portfolio demonstrating projects in ML model development, data analysis, and feature engineering.
• Solid proficiency in ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python. Experience with SQL and familiarity with data visualization libraries (e.g., Seaborn, ggplot2).
• Exceptional skills in analyzing complex data sets to develop ML models that effectively address business needs.
• Strong ability to communicate complex ML concepts and the results of analyses clearly to both technical and non-technical stakeholders.
• Demonstrated ability to work effectively in a team, showing adaptability and openness to feedback.