Senior Machine Learning Engineer

Job Description :

Responsibilities :

- Support BlueVine's business and research Data teams by designing and developing data-centric infrastructure tools to facilitate and enhance Data Analytics and Research, both in real-time and offline.

- Help design and implement next-generation ML workloads, focusing on modern, efficient Big Data technologies.

- Use pipeline orchestration tools such as AirFlow, ML platforms such as SageMaker, and data frameworks to design and develop first-in-class solutions for the financial sector.

- Design and develop end-to-end data pipelines, from data collection, through data validation and transformation, to making the data available to processes and stakeholders.

- Work closely with BlueVine's Data Science, Data Engineering, and Data Analytics teams.

- Work closely with BlueVine's other R& D teams to help incorporate industry best practices, define and enforce data governance procedures, and monitor system performance.

Requirements :

- Bachelor's or Master's in Computer Science or a related field.

- 5+ years of full-time work experience (not including internships, study, personal/school projects) as a Backend engineer/ML Infra engineer in a fast-paced, data-centric environment.

- 5+ years of hands-on Python programming experience (not including internships, study, personal/school projects).

- Experience with AWS ecosystem and container technology (e. g., Docker, K8S).

- Exceptional communication skills, ability to collaborate smoothly with and convey complex ideas in a clear way to people of different backgrounds.

- Be a quick learner, adaptable, and have the ability to work independently or as part of a team in a fast paced environment.

- Ability to quickly and independently learn new technologies, frameworks, and algorithms.

- Proactive, result-driven, and multi-tasker; creative but committed to meeting deadlines.

- Very good English, written and verbal.

Bonus points if you also have :

- Experience with AWS SageMaker.

- Experience with databases such as PostgreSQL, Redshift, Neptune.

- Experience with monitoring tools like Grafana, Sentry, and Opensearch.

- Experience working with Python ML libraries (e. g. Pandas, Numpy, Scikit Learn).

- Experience working with Airflow.

- Experience in working with Jenkins-based CI/CD.

- Experience with streaming and real-time analytics systems.