Why rinf.tech?

Why do we do what we do?

We inspire one another to share our tech-works in this amazing and abundant world. So we became developers, innovators, thinkers, software builders, and hardware makers!

Our Vision!

Founded in 2006 with 650+ engineers & global presence (8 delivery centers in Europe & North America) we strive to become a leading East-European technology partner for growing organizations in need of digital transformation of their products and services!

What you’ll do

• 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 expose deliver machine learning results to internal teams and Metro’s customers.
• Evaluate emerging machine learning technologies, frameworks, and trends, and introduce improvements to existing workflows.

What you need to be successful

• 7 years of hands-on experience in building and deploying machine learning models in production.
• 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.
• Expertise in GCP or other cloud platforms.
• 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).
• Understanding of ethical AI, bias mitigation, and data privacy principles.

Join the #PeopleofManyTalents #EngineerOfTheFuture