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
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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