Lead/Senior MLOps Engineer
Role: Lead/Senior MLOps Engineer
Location: remotely or from our Krakow office
Budget; 30-37 k net on b2b or 27-35 k gross on perm
About the job
We are building the largest global ground transportation marketplace platform to allow travellers to hail and book taxi rides from their preferred brands’ websites and mobile apps, by aggregating and normalising taxi and PHV fleets globally.
Developing, productionising and deploying ML models that enhance the capabilities of the marketplace & marketpay platform; e.g. demand-supply matching, pricing prediction, ETA, forecasting, dispatch system compensation, anomaly detection and auto-healing, is critical to successfully building and scaling out the marketplace globally!
We are looking for an ambitious MLOps Engineer to create and develop production-grade ML services and pipelines, using and adapting cutting-edge technologies, in a fast-paced agile and collaborative culture. You’ll be working closely alongside our data scientists, marketplace/marketpay software engineers and SRE, to help integrate and apply ML throughout the business.
The ideal candidate will have a strong background working with data products and experience building and running production-grade ML services.
● Lead the development and evolution of robust production-grade ML services, serving and training workflows and pipelines using industry best practices
● Build and manage processes and tooling to successfully serve, measure and monitor the quality and performance of ML models over time
● Make architecture, technology, tool, and language choices
● Continuously drive improvement, excellence and best practice in Machine learning / infrastructure within the company
● Optimize the performance of ML model training and serving workloads
● Conduct code reviews, code refactoring and improve model and infrastructure test coverage and maturity
● Troubleshoot complex bugs in distributed systems and pipelines
● Support data scientists transitioning their ML models into production
Experience / Skills
● Strong engineering background.
● Some experience deploying, serving and optimising ML models in production environments at scale. Seldon and Kubflow experience is a bonus!
● Knowledge and experience of software engineering practices (e.g. CI/CD, observability, monitoring, micro-service architecture principles, etc.)
● Experience with kubernetes-based deployment on Google Cloud Platform, AWS, Azure, or equivalent Cloud infrastructure providers and other technologies: Linux, Docker, Terraform IaC, gRPC, RESTful APIs
● Experience driving improvement, excellence and best practice in MLOps
● Skilled in developing production software in: Python (preferred), Go or Scala
● Familiarity building and serving models with ML toolkits like scikit-learn, TensorFlow, PyTorch, etc
● (Bonus) experience of ML model A/B testing and experimentation
● Excellent written and oral communication in English and ability to explain succinctly complex technical issues