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MLops Engineer IRC241640
Job | IRC241640 |
Location | Romania - Cluj-Napoca |
Designation | Lead Software Engineer |
Experience | 5-10 years |
Function | Engineering |
Skills | Apache Spark, AWS, Azure, Databricks, Google Cloud, Java, Kafka, Kubeflow, Kuberneetes, Machine Learning, Python, Scala |
Work Model: | Remote |
Description
Found at over 65,000 bars, restaurants and other social venues across North America and Europe, this app is bringing people together with fun, interactive music and entertainment solutions. Our flagship jukeboxes, paired with our extensive music catalog and mobile app, inspire millions of people every week to play the right song at the right time at their favorite hangouts.
Reinventing the jukebox for a new era. It’s been over two decades since we invented the commercial digital jukebox. Since then, we have continued to drive innovation, and push design boundaries – creating the first ever jukebox app that lets people play the perfect song right from their seat. And now, we’re taking this app to new places, like workspaces, breakrooms, schools and more — where people can choose the music, and create a vibe, together.
#LI-RC1
Requirements
• 5+ years of experience in machine learning, data engineering, or related roles with a focus on productionizing machine learning models.
• Strong proficiency in data engineering, particularly within Databricks, including experience with cluster management, job scheduling, and performance optimization.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Familiarity with CI/CD tools (e.g., Jenkins, GitLab CI) and infrastructure automation (e.g., Terraform, Ansible).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization/orchestration technologies (e.g., Docker, Kubernetes).
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.
• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. A Master’s degree is preferred.
Job Responsibilities
Key Responsibilities:
•Data Engineering & Databricks Management:
– Provide thought leadership in the management and optimization of Databricks environments, ensuring efficient and scalable data processing workflows.
– Offer expertise in designing, implementing, and maintaining data transformations and ETL processes within Databricks, supporting data science initiatives.
– Collaborate with data engineers to ensure data infrastructure supports machine learning model development and deployment.
• Model Development Support:
– Work closely with data scientists to understand model requirements and assist in developing machine learning models, ensuring they are production-ready.
– Provide guidance and support in feature engineering, model training, and validation processes.
– Help data scientists integrate their models with existing systems and APIs, enabling effective real-time inference.
• Model Deployment and Integration:
– Provide thought leadership in designing and implementing pipelines for the automated deployment of machine learning models, ensuring scalability and reliability.
– Facilitate the integration of models into production systems, focusing on seamless interaction with existing data and software infrastructure.
• Collaboration and Communication:
– Serve as a key advisor between data science and engineering teams, ensuring alignment in model development and deployment strategies.
– Document processes and best practices for model development, deployment, and data pipeline management.
– Communicate complex technical concepts to non-technical stakeholders and ensure that model deployment aligns with business objectives.
• Automation and Tooling:
– Develop and maintain automated workflows for data preprocessing, feature engineering, model training, and model validation within the Databricks environment.
– Implement and manage MLops tools and frameworks (e.g., MLflow, Kubeflow, TFX) to support streamlined model development and deployment.
We Offer
Empowering Projects: With 500+ clients spanning diverse industries and domains, we provide an exciting opportunity to contribute to groundbreaking projects that leverage cutting-edge technologies. As a team, we engineer digital products that positively impact people’s lives.
Empowering Growth: We foster a culture of continuous learning and professional development. Our dedication is to provide timely and comprehensive assistance for every consultant through our dedicated Learning & Development team, ensuring their continuous growth and success.
DE&I Matters: At GlobalLogic, we deeply value and embrace diversity. We are dedicated to providing equal opportunities for all individuals, fostering an inclusive and empowering work environment.
Career Development: Our corporate culture places a strong emphasis on career development, offering abundant opportunities for growth. Regular interactions with our teams ensure their engagement, motivation, and recognition. We empower our team members to pursue their career goals with confidence and enthusiasm.
Comprehensive Benefits: In addition to equitable compensation, we provide a comprehensive benefits package that prioritizes the overall well-being of our consultants. We genuinely care about their health and strive to create a positive work environment.
Flexible Opportunities: At GlobalLogic, we prioritize work-life balance by offering flexible opportunities tailored to your lifestyle. Explore relocation and rotation options for diverse cultural and professional experiences in different countries with our company.