Kayzen is the future of mobile marketing — building software that allows mobile app developers to connect with their users.
We are a B2B SaaS platform that allows companies to run mobile programmatic marketing in-house.
Programmatic marketing, put simply, is the process of automating the buying and selling of digital ads in real time. Programmatic in-housing takes this one step further by allowing advertisers to fully own the technology stack and skills required in this process.
Programmatic in-housing is still in its early days of adoption in the mobile advertising market. This is where we have impact!
Are you excited about data? Will you take on the challenge to help us make our organization become an ML first organization? Do you want to change the way we as an organization manage our data and do business? Are you interested in how billions of data points flow through various systems & data pipelines and how it is governed to generate knowledge and value? If you are a team player who strives for engineering and technical excellence and enjoys bringing innovations in a fast paced environment, we have a perfect job for you! If your answer is “yes” to all these questions, we would love to meet with you!
As our Machine Learning Engineering Lead, you will be part of the Machine Learning Engineering team, which is the bridge between the data science and engineering team. You will work directly with stakeholders to create innovative solutions for handling petabytes of data with billions of rows & joins. Your work can vary from advice on the big data platform and architecture they (need to) work on, to building scalable ML solutions by making use of state-of-the-art technologies.
Responsibilities, in the day-to-day work you will:
Lead a team of machine learning engineers, mentoring and guiding them to create a robust ML platform for a fast paced delivery.
Define solution architectures designs.
Apply state-of-the-art machine learning techniques to create insights and convert them into actions.
Develop code that is production-ready and produce our ML models in both bare-metal and the cloud environment.
Setting up and applying MLOps frameworks.
Hire and build a great ML engineering team.
Reduce manual effort and develop configuration-driven frameworks.
We are looking for a candidate with a minimum 10+ yrs of professional experience in creating and maintaining data pipeline architectures, identifying data related process improvements and building tools & frameworks that enable data science activities.
Bachelor's/Master’s degree in a quantitative field of Mathematics, Physics, Computer Science, Machine learning Engineering, Business Analytics, Information Management or related field.
Experience in leading teams and using agile methodologies in a fast-paced environment.
You know your way around relevant programming languages (SQL, Python, R, etc.), Machine Learning techniques (Neural Networks, Random Forest, etc.), Cloud computing (AWS, Azure or GCP) and ML frameworks (MLflow, PyTorch, Tensorflow, etc.).
Familiar with Git, command line, SQL & NoSQL, Spark, Docker and API frameworks
Proven record of strong leadership, management and communication skills
You have proven affinity with data
You have strong analytical and problem-solving skills
You can translate business requirements into data solutions
You have excellent stakeholder management skills.
Previous experience with ad-tech is a plus.
What do we offer?