Senior Machine Learning Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Today, The Kraft Heinz Company is building a new legacy by investing in a robust Digital infrastructure to revolutionize the food and beverage industry. We are on a journey to create a digitally-powered, agile-enterprise – all while honoring a 150-year heritage and a portfolio of 200 iconic brands. At the heart of this journey is our ambition to create an environment where powerful AI solutions augment humans and where small mission-based teams relentlessly pursue tangible solutions for our consumers, customers, and the enterprise.

That ambition requires us to create a modern cloud and data ecosystem - a one of its kind that becomes the neural network of our company. We want you to bring your tech-self to us. We use Python, R, Spark, React, Tableau, Snowflake, Azure, and others to solve our business challenges. You can look forward to high-impact, no bureaucracy, entrepreneurial work – done in small teams – and a unique opportunity to create something bold, something awesome, something inventive -- and something globally impactful.

WHAT YOU’LL DO

The Senior Machine Learning Scientist prototypes and develops machine learning models by utilizing state of the art tools/algorithms and methodologies following DevOps and a test-driven development process. Machine Learning Scientist is the key role to apply machine learning models at scale. At Kraft Heinz, Machine Learning Scientists work in close collaborations with the Machine Learning Engineers and guide them to not only focus on model performance but also delivery stability, reproductivity and scalability of a software product.

• Develop, own, implement and deploy state-of-the art ML algorithms and other predictive models which will serve as a guiding light for change and improvement
• Own and integrate disruptive technologies (AI/ML, Automation, Optimization) focused on fundamentally transforming the way in which we operate
• setting the technical bar at an application level
• Serve as an integral part of the Digital Revolution by being an advisor/leader of an agile pod
• Collaborate with ML engineers to test and scale new algorithms through pilots and later industrialize the solutions at scale to the comprehensive fashion network of the Group
• Design, develop and maintain the framework for analytical pipeline
• Work with ML Engineers to help common components to address pain points in machine learning project, like model lifecycle management, feature store and data quality evaluation
• Provide input and help implement framework and tools to improve data quality
• Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, designers, product managers and others to build the AI ecosystem within the Group
• Deliver on time, demonstrating strong commitment to deliver on the team mission and agreed backlog

WHO YOU ARE

• S. or Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Math or related topics
• 3+ years of experience working in a Machine Learning, Data Scientist or Software Engineer role
• Ability to create and build proof of concept machine learning models into scalable solutions
• Ability to apply software development best practice into machine learning project, including unit test, DevOps integration, release management, test driven development, etc.
• Ability to automate development process of machine learning project by leverage state of art tools and technology like container, continuous integration and delivery, orchestration tools etc.
• Experience with TensorFlow is preferred
• Experience in SQL, relational databases, database concepts, dimensional modeling and database design
• Intermediate in one or more programming languages used for modeling such as Java, C++, Python, R, Scala .
• Familiar with one or more machine learning or statistical modeling tools
• Experience with cloud platforms (Azure, AWS, GCP, …)