ML Engineer at Dunnhumby Limited

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

05 May, 26

Salary

0.0

Posted On

04 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, Kubernetes, Cloud Deployment, Docker, Data Science, DevOps, CI/CD, Shell Scripting, Big Data, Scikit-learn, TensorFlow, PyTorch, Spark, Collaboration, Communication

Industry

technology;Information and Media

Description

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro. We are seeking a talented and passionate Machine Learning Engineer to join our growing team. You will play a key role in designing, developing, and deploying machine learning (ML) solutions that drive business value. This role requires expertise in Python programming, container orchestration with Kubernetes, and cloud deployment. 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. Qualifications: Bachelor's/Master's degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience). Proven experience with Python programming & PySpark for data science and machine learning. Experience with DevOps Concepts CI/CD and Shell Scripting Experience with container orchestration platforms like Kubernetes and containerization technologies like Docker. Experience with cloud deployment (e.g., AWS, GCP, Azure). Good understanding of machine learning algorithms and concepts. Excellent communication and collaboration skills. Ability to work independently and as part of a team. Bonus points: Working knowledge of ML algorithms Experience developing self-service applications. Experience with model monitoring and observability tools. What you can expect from us We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off. You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn. And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. Our approach to Flexible Working At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work. We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process. For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)

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Responsibilities

Design, develop, and deploy production-ready machine learning models. Collaborate with data scientists and software engineers to implement ML solutions effectively.