Job Description

We are using technology and automation to disrupt the traditional food industry. We are focused on building an operating system for Cloud Kitchens - using the most innovative technologies - to provide the best food experiences for our customers. You will enjoy working with us, if:

• You are passionate about using technology to solve customer problems
• You are a software craftsman or craftswoman who is obsessed with high quality software
• You have a flair for good design and architecture
• You are unafraid of rearchitecting or refactoring code to improve it
• You are willing to dive deep to solve complex software issues
• You are a teacher and mentor

We are looking for someone to lead a team of talented Data Scientists in solving the toughest problems in food tech today. The role would require someone who has led similar teams and created and deployed high-quality data, ML, and AI solutions at scale. This role will involve hands-on work and daily working sessions with the data scientists to create, improve, and debug ML models across multiple business domains. The person should be able to visualize thehigh-level picture and give direction, while also not being afraid to get their hands dirty and remove roadblocks for team members.Responsibilities:

• Provide strategic direction and oversee the execution of machine learning initiatives to address specific business needs.
• Lead and manage a team of Machine Learning engineers in designing, developing, and implementing machine learning models.
• Collaborate with PMs and cross-functional teams to understand requirements and strategize innovative solutions
• Ensure the development and maintenance of robust, scalable, and reusable code, with proper version control.
• Operate in a hands-on capacity when necessary.

Requirements:

• Demonstrated track record in designing, building, and deploying ML models with a focus on accuracy and scalability.
• Strong hands-on experience in ML algorithms libraries like Pytorch, Tensorflow/Keras, and Scikit-Learn.
• Solid understanding of AI/ML techniques related to Regression, Classification, Gradient Boosting, NLP, and Computer Vision.
• Good knowledge of using Optimization with OR Tools. Strong hands-on skills in Data Analytics, Feature Engineering, and EDA/Visualization using libraries like Pandas, Matplotlib, Plotly, etc.
• Understanding of Dockerization, and REST APIs.

Good-to-have:

• Strong stakeholder management skills.
• Experience in building Time-Series Forecasting Models and Market Mix Models.
• Interest in improving ML fluency in the larger organization and setting best practices.

TAAS Partners