Lead - Machine Learning

3 weeks ago

Bangalore, India GeekTrust Full time

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.

(ref:hirist.tech)

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