dunnhumby is hiring for a fresher entry level Machine Learning Engineer

Position:

• ML Engineer

Company:

• dunnhumby

Location:

• Gurgaon, Haryana, India

Job Type:

• Full-time

Job Mode:

• Entry level

Job Requisition ID:

• Not provided

Years of Experience:

• Not specified

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Company Description

• dunnhumby is a global leader in Customer Data Science, specializing in empowering businesses to excel in the modern data-driven economy by prioritizing the customer. With extensive expertise in the retail sector, dunnhumby leverages vast, multidimensional data to enable businesses across various industries to adopt a customer-centric approach.
• Founded on a rich legacy in retail, one of the most competitive markets, dunnhumby supports renowned brands worldwide, such as Tesco, Coca-Cola, Meijer, Procter & Gamble, and Metro.
• The company employs nearly 2,500 experts spread across offices in Europe, Asia, Africa, and the Americas, focusing on transforming businesses through data science.
• Committed to fostering growth and innovation, dunnhumby’s mission is to help businesses become advocates for their customers, driving sustainable growth and reimagining their roles in the marketplace.

Profile Overview

• dunnhumby is seeking a passionate and skilled Machine Learning Engineer to join their team. This role involves designing, developing, and deploying machine learning solutions that significantly impact business value.
• The ideal candidate will possess strong expertise in Python programming and experience with container orchestration using Kubernetes and cloud deployment.
• Key responsibilities include:
  • Developing production-ready ML models using Python libraries like Scikit-learn, TensorFlow, and PyTorch.
  • Managing ML model deployment in cloud environments and optimizing their performance.
  • Collaborating with data scientists, software engineers, and product managers to implement ML solutions effectively.
  • Utilizing Docker and Kubernetes for containerizing ML models to enhance scalability and portability.
  • Staying updated on advancements in MLOps, data science, and machine learning to drive innovation within the team.

Qualifications

• Essential qualifications for this position include:
  • A Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent experience.
  • Proven experience with Python programming and PySpark for data science and machine learning applications.
  • Familiarity with DevOps concepts, including CI/CD and shell scripting.
  • Proficiency in using container orchestration platforms like Kubernetes and containerization technologies like Docker.
  • Experience with cloud deployment platforms such as AWS, GCP, or Azure.
  • A solid understanding of machine learning algorithms and concepts.
  • Excellent communication and collaboration skills, with the ability to work both independently and as part of a team.

Any Additional Info

• Additional qualifications and benefits for this role include:
  • Working knowledge of ML algorithms and experience in developing self-service applications.
  • Familiarity with model monitoring and observability tools is advantageous.
  • dunnhumby offers a comprehensive rewards package, including flexible working hours and your birthday off.
  • The company provides an environment that combines cutting-edge technology with a small-business feel, allowing for experimentation and learning.
  • Commitment to diversity and inclusion is evidenced by thriving networks such as dh Gender Equality Network, dh Proud, dh Family, dh One, and dh Thrive.
  • dunnhumby values work-life balance and offers flexible working options to help employees manage their commitments outside of work. This can be discussed with the recruiter during the hiring process.

Responsibilities:

• Design, develop, and deploy production-ready ML models using Python libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and big data frameworks (e.g., Spark).
• Manage the deployment of ML models to the cloud environment and optimize the performance of ML models.
• Collaborate with data scientists, software engineers, and product managers to ensure successful implementation of ML solutions.
• Leverage Docker and Kubernetes to containerize ML models for scalability and portability.
• Stay up-to-date on the latest advancements in MLOps, data science, and machine learning.

Additional Sections:

Rewards and Benefits:

• Comprehensive rewards package with flexible working hours and additional personal perks.
• Emphasis on diversity and inclusion with active support networks for various groups within the company.
• Investment in state-of-the-art technology and a collaborative, innovative work environment.
• Opportunities for professional growth and development through cutting-edge projects and responsibilities.

Flexible Working:

• dunnhumby supports a balanced work-life approach, encouraging employees to manage their professional and personal commitments effectively.
• Flexible working options are available and can be discussed during the recruitment process to accommodate individual needs.

Contact Information:

• For an informal and confidential discussion, potential candidates can contact Stephanie Winson at stephanie.winson@dunnhumby.com to explore how the recruitment process can be tailored to meet their needs.

Please click here to apply.

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