Key Responsibilities
- Take ownership of the technical direction and execution of machine learning projects within the Data Science team;
- Mentor and support junior engineers and data scientists enabling their growth and success;
- Establish best practices for software design architecture and MLOps;
- Design and optimize end-to-end machine learning pipelines for training testing and deployment in production environments;
- Ensure seamless deployment of machine learning models and implement monitoring solutions to track performance accuracy and drift over time;
- Collaborate with data scientists to transition experimental models to production-grade solutions;
- Work closely with other software/data engineers and product teams to ensure effective delivery of machine learning products;
- Collaborate with other teams and gather requirements to solve complex customer problems with machine learning;
- Maintain and scale machine learning infrastructure using GCP;
- Implement robust security measures to protect data privacy;
- Create and maintain APIs or other interfaces to deliver machine learning results to internal teams and Metros customers;
- Evaluate emerging machine learning technologies frameworks and trends and introduce improvements to existing workflows.
Qualifications :
Education
Bachelors or Masters degree in Computer Science Software Engineering or equivalent practical experience.
Work Experience & Skills
- 8 years of hands-on experience in building and deploying machine learning models in production. Strong technical background and current modern BI and reporting technologies;
- Proven experience in leading or mentoring technical teams;
- Proficiency in Python Go and machine learning frameworks;
- Strong understanding of MLOps tools and practices including CI/CD pipelines model versioning and monitoring;
- Proficient with data transformation tools (preferable dbt);
- Expertise in GCP services such a Cloud Run Kubernetes BigQuery and VertexAI;
- Solid skills in API development and automated testing;
- Exceptional problem-solving abilities and a proactive team-oriented mindset;
- Strong communication and collaboration skills with the ability to explain technical concepts to non-technical stakeholders;
- Leadership qualities with a track record of driving projects and guiding teams toward success;
- Experience in optimizing models for performance (e.g. inference speed resource usage);
Additional Information :
Nice-to-Have
Understanding of ethical AI bias mitigation and data privacy principles.
Remote Work :
No
Employment Type :
Full-time
Key ResponsibilitiesTake ownership of the technical direction and execution of machine learning projects within the Data Science team; Mentor and support junior engineers and data scientists enabling their growth and success;Establish best practices for software design architecture and MLOps;Design ...
Key Responsibilities
- Take ownership of the technical direction and execution of machine learning projects within the Data Science team;
- Mentor and support junior engineers and data scientists enabling their growth and success;
- Establish best practices for software design architecture and MLOps;
- Design and optimize end-to-end machine learning pipelines for training testing and deployment in production environments;
- Ensure seamless deployment of machine learning models and implement monitoring solutions to track performance accuracy and drift over time;
- Collaborate with data scientists to transition experimental models to production-grade solutions;
- Work closely with other software/data engineers and product teams to ensure effective delivery of machine learning products;
- Collaborate with other teams and gather requirements to solve complex customer problems with machine learning;
- Maintain and scale machine learning infrastructure using GCP;
- Implement robust security measures to protect data privacy;
- Create and maintain APIs or other interfaces to deliver machine learning results to internal teams and Metros customers;
- Evaluate emerging machine learning technologies frameworks and trends and introduce improvements to existing workflows.
Qualifications :
Education
Bachelors or Masters degree in Computer Science Software Engineering or equivalent practical experience.
Work Experience & Skills
- 8 years of hands-on experience in building and deploying machine learning models in production. Strong technical background and current modern BI and reporting technologies;
- Proven experience in leading or mentoring technical teams;
- Proficiency in Python Go and machine learning frameworks;
- Strong understanding of MLOps tools and practices including CI/CD pipelines model versioning and monitoring;
- Proficient with data transformation tools (preferable dbt);
- Expertise in GCP services such a Cloud Run Kubernetes BigQuery and VertexAI;
- Solid skills in API development and automated testing;
- Exceptional problem-solving abilities and a proactive team-oriented mindset;
- Strong communication and collaboration skills with the ability to explain technical concepts to non-technical stakeholders;
- Leadership qualities with a track record of driving projects and guiding teams toward success;
- Experience in optimizing models for performance (e.g. inference speed resource usage);
Additional Information :
Nice-to-Have
Understanding of ethical AI bias mitigation and data privacy principles.
Remote Work :
No
Employment Type :
Full-time
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