Lead Software Engineer (MLOps)

Tasks:

- Hiring and leading the Data Engineering and MLOps team;

- Developing scalable and reliable ML infrastructure components to facilitate the deployment of ML models;

- Closely cooperating with the ML team, core platform developers, and architects for the maximum impact across the organization;

- Being a critical resource to implement the research team's ideas and bring them to market.

Tech stack on the project: Python, ML APIs, Docker, Kubernetes/OpenShift, Azure/AWS/Google Cloud, MLflow, Kubeflow, Kafka, Elasticsearch, Kibana, Grafana, Prometheus, Splunk.

Must-haves:

- Experience in building scalable and reliable ML infrastructure components and data ingestion and processing pipelines for 4+ years;

- Experience in deploying ML APIs/containers – such as Docker, Kubernetes, or OpenShift – to the public cloud (Azure, AWS, or Google Cloud);

- Experience with ML lifecycle platforms (MLflow, Kubeflow);

- Experience in designing data processing pipelines using Kafka, Elasticsearch, and Kibana;

- Knowledge of any tool for logging and monitoring, such as Grafana, Prometheus, Splunk, etc.;

- Experience with Python;

- Level of English – Intermediate.

Nice-to-naves:

- Experience with serverless platforms, such as AWS Lambda, Google Cloud Functions, Nuclio, Knative, etc.;

- Knowledge of deployment management tools, such as Terraform or Helm;

- Experience with Data Science tools in an AWS environment;

- Experience in progressive delivery, such as A/B testing, Canary deployment, and multi-armed bandit;

- Experience in managing Linux systems – the customer uses Ubuntu/Debian for bare metal servers and Amazon Linux in EKS and EC2 instances;

- Experience with a bare-metal Kubernetes cluster.

- Cooperation with such businesses as Samsung, Johnson & Johnson, Ryanair, Europcar, TUI, Verivox, Media Markt, Shypple, etc. This project is just your beginning here – working with us means reliability and prospects;

- Excellent teams with streamlined processes and an opportunity to change the project. There are also systems of mentoring and adaptation for each new employee;

- Many different ways to grow – you can develop expertise in different business domains and improve as a specialist or a manager. Transparent performance review and assessment systems will allow you to determine your development path and plan your growth;

- Flexible start of the working day: from 7 AM to 11 AM. You can telecommute, work at the office, or opt for a hybrid schedule – whatever is convenient for you;

- Referral programs and an opportunity to additionally earn up to $1,500 per month by participating in the company's activities;

- Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated;

- Such perks as private health insurance, English language courses, and certification compensation (AWS, PMP, etc.).