Senior Machine Learning Engineer

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together - when we combine your strengths with ours - is unstoppable. Are you ready to join a team that dreams as big as you do?

Senior Machine Learning Engineer/MLOps Engineer (Band VI)

Description: As a Senior MLE/MLOps Engineer, you are a leader who interacts with end-to-end processes of multiple Machine Learning models, incluiding coding Best Practices, DevOps pipelines, Cloud and Software Architecture; influencing its design, development, deployment, and operation; mainly from a technical and managerial side.

**Skills**:

- Preferred qualifications_
- Expertise in Machine Learning Systems Design
- Knowledge in Software design or architecture (design patterns, reliability, scaling) of new and existing systems
- Knowledge in Full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Expertise in Git and branching strategies
- Experience in Microsoft Azure Cloud or any other cloud platform (ML pipelines)
- Data Science and/or Data Engineering foundations
- Decision making and leadership in a high performance and changing environment
- High English Level (B2)
- Experience as a mentor, tech lead or leading an engineering team
- Excellent backlog prioritization (products, reports, technical features)
- Technical and thought leadership
- An awesome team player and active listener
- Self-driven
- Emotional Intelligence
- Curious and fast learner
- Nice To Have_
- Expertise in Machine Learning end to end pipelines
- Strong Python coding skills (Object Oriented Programming)
- Communication protocols for ML products
- REST APIs
- Python Web frameworks (Django, Flask, FastAPI)
- Streaming (Kafka, RabbitMQ, others)
- Batch delivery and Offline delivery
- Containerization platforms (Docker / Kubernetes)
- Expertise in Infrastructure as Code (Terraform, Ansible)
- CI/CD/CT (GitHub Actions, Jenkins, Ansible, Circle CI, etc.)
- Observability and Monitoring (for Infrastructure, Data, ML and KPIs)
- Experience working in Agile Software Development
- Expertise in Machine Learning modeling techniques
- Databricks ecosystem applied for ML products
- Expertise in SQL & NoSQL Databases
- Flexible adoption of innovative technologies (GenAI, Computer Vision, LLMs, and others)
- Big Data technologies such as Hadoop, Spark, Pig, Hive, etc.
- Big Data infrastructure (data lakes, Snowflake, Databricks, Blob Storage, S3)
- ML libraries/frameworks such as Tensorflow, Keras, PyTorch, etc.

**Responsibilities**:

- Technical_
- Define and lead long-term vision for ML Products
- Executive presentations to Senior Leadership (MLOps Steerco, Sprint Reviews, etc.)
- Lead meetings, sessions, and workshops with a solid technical foundation
- Develop and implement software solutions that leverage workflow automation
- Actively engage and participate in software architecture and design
- Participate in code reviews and provide constructive feedback to peers
- Write clean, efficient, and well-documented code that adheres to industry best practices
- Stay up to date with emerging technologies and industry trends to ensure our software solutions remain at the forefront of the industry, in topics like Monitoring, Observability, ML lifecycle, Architecture and related
- Management_
- Lead, mentor, challenge and grow other MLOps Engineers / Data Scientists on the team
- Create work plans (timelines, roadmaps, resources, budget) based on agile methodologies to address different challenges at the software level