Lead - Machine Learning
1 month ago
About the company :
Tesco PLC is a British multinational groceries and general merchandise retailer headquartered in Welwyn Garden City, England.
In 2011 it was the third-largest retailer in the world measured by gross revenues and the ninth-largest in the world measured by revenues.
Skill Sets :
- Understanding of Data Structures, Data Modeling, and Software Architecture.
- Strong ML fundamentals and understanding of model architectures and operations.
- Ability to architect software and ML systems at scale.
- Experience in Data Engineering.
- Knowledge of various ML and Deep Learning algorithms and techniques.
- Proficiency in Python scientific computing libraries.
- Experience with implementing ML workflows in the cloud.
- Familiarity with container technologies like Docker and Kubernetes.
- Excellent communication skills.
- Collaboration with product, design, and backend engineering teams.
- Enthusiastic about learning new skills and technologies.
Responsibilities :
Software and ML System Architecture :
- Design and architect software and machine learning systems at scale, considering factors such as performance, scalability, and reliability.
- Define system architectures that support large-scale data processing and machine learning workflows.
Data Engineering :
- Lead data engineering efforts to build robust data pipelines, ETL processes, and data warehouses.
- Design and optimize data storage, retrieval, and transformation mechanisms to support machine learning workflows and analytics.
Machine Learning Development :
- Develop and implement advanced machine learning algorithms and models to solve complex business problems.
- Apply various ML and deep learning techniques to analyze large datasets and derive actionable insights.
Model Architectures and Operations :
- Design and deploy machine learning models at scale, ensuring efficient model training, inference, and monitoring.
- Implement model architectures that are optimized for performance, accuracy, and interpretability.
Cloud-Based ML Workflows :
- Develop and implement machine learning workflows in cloud environments such as AWS, Azure, or Google Cloud Platform.
- Utilize cloud-based ML services and platforms to streamline model development, deployment, and management.
Collaboration and Leadership :
- Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to define requirements, prioritize tasks, and deliver solutions.
- Provide technical leadership and mentorship to junior team members.
Research and Innovation :
- Stay updated on the latest advancements in machine learning, deep learning, and data engineering technologies.
- Explore new algorithms, techniques, and tools to drive innovation and improve our ML capabilities.
Requirements :
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related field.
- Advanced degree (Master's or Ph.D.) preferred.
- 10 to 20 years of experience in machine learning, data engineering, and software architecture. Strong understanding of data structures, data modeling, and software architecture principles.
- Solid fundamentals in machine learning, with expertise in various ML and deep learning algorithms and techniques.
- Experience architecting and building scalable software and ML systems.
- Proficiency in Python and Python scientific computing libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow, PyTorch).
- Experience with cloud platforms and services for implementing ML workflows (e.g., AWS SageMaker, Azure ML, Google Cloud AI Platform).
- Excellent problem-solving skills and analytical thinking.
- Strong communication and collaboration abilities, with the ability to work effectively in a team environment.
- Demonstrated leadership skills and ability to mentor and coach junior team members.
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