AI/ML Pipeline Developer

Job Title: AI/ML Pipeline Developer

We are seeking a highly skilled and experienced AI/ML pipeline developer to join our global team. As an AI/ML pipeline developer, you will be responsible for designing and developing custom machine learning and deep learning models for business-specific problems.

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• Design and develop scalable AI/ML pipelines for data ingestion, preprocessing, training, testing, deployment, and monitoring.\
• Collaborate with cross-functional teams to integrate AI solutions into real-world products.\
• Ensure high-performance, scalable, and production-ready deployment using MLOps practices.\
• Optimize models with advanced techniques (hyperparameter tuning, distributed training, GPU optimization).\
• Document technical processes, architectures, and pipeline workflows for reproducibility and knowledge sharing.\
• Stay up-to-date with the latest innovations in LLMs, generative AI, and automation frameworks.\
• Develop and maintain AI/ML pipelines using Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, and other relevant technologies.\
• Prioritize and manage multiple projects simultaneously, ensuring timely delivery and quality results.\
• Maintain accurate records of project progress, timelines, and deliverables.\
• Collaborate with data scientists, engineers, and product managers to identify areas for process improvement.\
• Contribute to research initiatives and adopt best practices in AI/ML development.\
• Participate in code reviews, providing constructive feedback and suggestions for improvement.\
• Stay current with industry trends, emerging technologies, and methodologies.\
• Provide support and guidance to junior developers and contribute to their growth and development.\
• Develop and maintain documentation, including user manuals, technical guides, and API references.\
• Integrate AI/ML solutions with existing infrastructure, including databases, APIs, and third-party services.\
• Maintain a clean and organized codebase, adhering to coding standards and best practices.\
• Work closely with QA engineers to ensure that AI/ML solutions meet quality and performance standards.\
• Develop and implement automated testing frameworks for AI/ML solutions.\
• Collaborate with security teams to ensure that AI/ML solutions meet security and compliance requirements.\
• Monitor and report on AI/ML solution performance, identifying areas for improvement and recommending enhancements.\
• Develop and maintain dashboards and reports to track key performance indicators (KPIs) and metrics.\
• Communicate effectively with stakeholders, including executive leaders, product managers, and customers.\
• Present complex technical information in a clear and concise manner.\
• Travel as required for meetings, workshops, and conferences.\
• Perform other related duties as assigned.\
• The ideal candidate should have a strong background in AI/ML, programming languages, and software development methodologies.\
• Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker), and orchestration (Kubernetes) is a plus.\
• Familiarity with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines is desirable.\
• A bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, or related field is required.\
• 5+ years of experience in AI/ML development, preferably with a focus on pipeline development.\
• Proficiency in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, and other relevant technologies.\
• Strong problem-solving skills, attention to detail, and ability to work independently.\
• Excellent communication, collaboration, and leadership skills.\
• Bachelor's/Master's in Computer Science, Artificial Intelligence, Data Science, or related field.\
• 5+ years of hands-on experience in developing AI/ML solutions.\
• Strong programming expertise in Python and frameworks like PyTorch, TensorFlow, Scikit-learn, Hugging Face.\
• Proven track record in building and managing ML pipelines (Airflow, Kubeflow, MLflow, Prefect, etc.).\
• Proficiency in data preprocessing, feature engineering, and model evaluation techniques.\
• Hands-on experience with cloud AI/ML platforms (AWS Sagemaker, Azure ML, or GCP Vertex AI).\
• Familiarity with containerization and orchestration (Docker, Kubernetes).\
• Strong problem-solving ability and ability to work independently in a remote, fast-paced environment.\
• Preferred Skills:\
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  • Experience in fine-tuning Large Language Models (LLMs).\
  • Exposure to real-time/streaming data processing (Kafka, Spark Streaming).\
  • Knowledge of microservices and API development for model integration.\
  • Experience with generative AI and reinforcement learning techniques.\
  • Develop and maintain scalable AI/ML pipelines for data ingestion, preprocessing, training, testing, deployment, and monitoring.\
  • Collaborate with cross-functional teams to integrate AI solutions into real-world products.\
  • Ensure high-performance, scalable, and production-ready deployment using MLOps practices.\
  • Optimize models with advanced techniques (hyperparameter tuning, distributed training, GPU optimization).\
  • Document technical processes, architectures, and pipeline workflows for reproducibility and knowledge sharing.\
  • Develop and maintain AI/ML pipelines using Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, and other relevant technologies.\
  • Continuously evaluate and improve AI/ML solutions based on performance metrics and user feedback.\
  • Support and collaborate with data scientists, engineers, and product managers to identify areas for process improvement.\
  • Stay up-to-date with industry trends, emerging technologies, and methodologies.\
  • Provide support and guidance to junior developers and contribute to their growth and development.\
  • Develop and maintain documentation, including user manuals, technical guides, and API references.\
  • Integrate AI/ML solutions with existing infrastructure, including databases, APIs, and third-party services.\
  • Work closely with QA engineers to ensure that AI/ML solutions meet quality and performance standards.\
  • Develop and implement automated testing frameworks for AI/ML solutions.\
  • Collaborate with security teams to ensure that AI/ML solutions meet security and compliance requirements.\
  • Monitor and report on AI/ML solution performance, identifying areas for improvement and recommending enhancements.\
  • Communicate effectively with stakeholders, including executive leaders, product managers, and customers.\
  • Present complex technical information in a clear and concise manner.\
  • Travel as required for meetings, workshops, and conferences.\
  • Perform other related duties as assigned.\
  • The ideal candidate should have a strong background in AI/ML, programming languages, and software development methodologies.\
  • Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker), and orchestration (Kubernetes) is a plus.\
  • Familiarity with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines is desirable.\
  • A bachelor's or master's degree in Computer Science, Artificial Intelligence, Data Science, or related field is required.\
  • 5+ years of experience in AI/ML development, preferably with a focus on pipeline development.\
  • Proficiency in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, and other relevant technologies.\
  • Strong problem-solving skills, attention to detail, and ability to work independently.\
  • Excellent communication, collaboration, and leadership skills.\