AI/ML Lead and Architect for Machine Learning Modeling
3 weeks ago
Job Summary:
We are seeking a highly experienced AI/ML Lead and Architect to join our team at Squareroot Consulting Pvt. Ltd. This role will involve designing, developing, and deploying scalable machine learning models that directly impact business outcomes.
Key Responsibilities:
• Lead the development and architecture of machine learning models and AI systems to address specific business needs.
• Design, implement, and optimize machine learning algorithms and predictive models across a variety of use cases (classification, regression, clustering, etc.).
• Manage and mentor a team of machine learning engineers, data scientists, and AI developers, ensuring technical excellence and growth.
• Collaborate with data engineers to design data pipelines that support machine learning model development and deployment.
• Own the end-to-end machine learning lifecycle, including data collection, feature engineering, model training, validation, testing, deployment, and monitoring.
• Ensure scalability, accuracy, and performance of models in production environments through continuous optimization and retraining.
• Monitor model drift, performance degradation, and work on improvements and updates to keep models reliable.
• Integrate models into larger AI systems and collaborate with software engineering teams to ensure smooth deployment and scaling of ML systems.
• Stay up-to-date with the latest machine learning research and advancements, applying innovative techniques to improve model accuracy and performance.
• Communicate model insights and technical strategy to non-technical stakeholders, including executives, product managers, and business leaders.
• Develop and maintain a roadmap for AI and machine learning initiatives, ensuring alignment with organizational goals.
Qualifications:
• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field (Ph.D. preferred).
• 8+ years of experience in AI/ML with a strong focus on machine learning model development, optimization, and deployment.
• Proven track record in machine learning model development (classification, regression, clustering, NLP, etc.), and experience with deep learning techniques.
• Proficiency in machine learning frameworks such as TensorFlow, Keras, PyTorch, and libraries like scikit-learn.
• Extensive experience in Python, R, and familiarity with SQL and NoSQL databases.
• Experience with cloud-based ML platforms like AWS SageMaker, Google Cloud AI, or Azure Machine Learning.
• Expertise in MLOps practices for model versioning, CI/CD pipelines, model monitoring, and maintaining machine learning models in production.
• Solid understanding of data preprocessing techniques, feature engineering, and data pipeline management.
• Experience in model evaluation metrics, A/B testing, hyperparameter tuning, and cross-validation techniques.
• Strong leadership and communication skills to effectively guide teams and work with cross-functional stakeholders.
• Experience working with large datasets and distributed computing systems (Hadoop, Spark) is preferred.
• Experience in specific domains such as NLP, computer vision, or time series analysis is a plus.
Preferred Skills:
• Strong background in statistical analysis and data science methodologies.
• Hands-on experience with reinforcement learning or advanced deep learning architectures (e.g., transformers, GANs).
• Familiarity with big data ecosystems and tools like Hadoop, Spark, and Kafka.
• Ability to manage and implement end-to-end AI/ML workflows, including experimentation and production pipelines.
Soft Skills:
• Analytical mindset with excellent problem-solving skills.
• Strong ability to communicate complex concepts to non-technical stakeholders.
• Proven experience in project management and team leadership.
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