ΠΡΠ° Π²Π°ΠΊΠ°Π½ΡΠΈΡ Π² Π°ΡΡ ΠΈΠ²Π΅
ΠΠΎΡΠΌΠΎΡΡΠ΅ΡΡ ΠΏΠΎΡ ΠΎΠΆΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ βΠΎΠ±Π½ΠΎΠ²Π»Π΅Π½ΠΎ 7 Π΄Π½Π΅ΠΉ Π½Π°Π·Π°Π΄
Senior Machine Learning Engineer (MLOps)
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Senior Machine Learning Engineer (MLOps): Building scalable, secure, production-ready ML platforms and recommendation systems with an accent on PySpark optimization, Azure cloud services, and automated ML pipelines. Focus on tuning Spark clusters, designing CI/CD workflows, and establishing reproducible model deployment and governance practices.
Location: Bogota, Colombia; remote role
Company
is a global business and technology transformation partner delivering engineering, AI, cloud, data, and digital transformation services across more than 50 countries.
What you will do
- Translate business requirements into scalable AI/ML and data engineering solutions in collaboration with stakeholders, data scientists, and engineering teams.
- Lead technical discussions, solution design workshops, and architectural reviews for end-to-end ML and MLOps implementations.
- Design, build, and maintain secure, production-ready ML platforms and infrastructure across cloud environments.
- Develop reusable ML frameworks, templates, and engineering best practices for model development, deployment, and operationalization.
- Optimize large-scale PySpark applications and tune Spark clusters for performance, scalability, reliability, and cost efficiency.
- Build CI/CD pipelines and establish MLOps practices covering model training, testing, deployment, monitoring, version control, experiment tracking, model registry, governance, and reproducibility.
Requirements
- 6β10 years of experience in data engineering, MLOps, software engineering, DevOps, cloud platforms, or distributed data processing.
- Masterβs degree in computer science, data science, data engineering, or a related field.
- Hands-on experience optimizing PySpark workloads and tuning Spark cluster performance.
- Experience with Azure Databricks, Apache Spark, Azure Machine Learning, Azure DevOps, Python, SQL, and CI/CD tools.
- Experience developing and deploying supervised machine learning models, including price recommendation and billing recommendation systems.
- Strong client-facing communication skills, requirements-gathering experience, Agile development knowledge, and the ability to balance architecture, development, operations, and strategic planning.
Culture & Benefits
- Work with a global team of engineers, scientists, and architects on engineering and research-driven projects.
- Contribute to AI, generative AI, cloud, and data initiatives across multiple industries.
- Participate in projects involving autonomous vehicles, robotics, and enterprise technology transformation.
- Join a diverse organization with more than 340,000 team members across over 50 countries.