Job Summary
We are seeking a skilled and motivated Machine Learning Engineering Engineer 2 to join our growing team. This role is ideal for an individual with a strong foundation in machine learning principles and a passion for building and deploying innovative solutions within the IT / Technology industry.
Key Responsibilities
The responsibilities of this role will encompass a range of tasks related to the development, implementation, and maintenance of machine learning models and pipelines. The candidate will collaborate with cross-functional teams to ensure the successful integration of machine learning solutions into our existing infrastructure.
Required Skills & Qualifications
- AI/ML: Demonstrated proficiency in Artificial Intelligence and Machine Learning concepts, including model selection, training, evaluation, and deployment.
- Scikit-learn: Experience utilizing Scikit-learn for various machine learning tasks, including data preprocessing, model selection, and evaluation.
- PyTorch: Familiarity with PyTorch, a widely used deep learning framework, for building and training complex neural networks.
- TensorFlow: Experience with TensorFlow, another popular deep learning framework, for developing and deploying machine learning models at scale.
- LLM: Understanding of Large Language Models (LLM) and their applications.
- ETL: Knowledge of ETL (Extract, Transform, Load) processes for data preparation and integration.
- Big Query: Experience with BigQuery for querying and analyzing large datasets.
- Data Flow: Familiarity with Data Flow for building and managing data processing pipelines.
- Python: Strong programming skills in Python, a versatile language widely used in machine learning.
- Airflow: Experience with Airflow for orchestrating and scheduling complex data workflows.
- PySpark: Proficiency in PySpark for distributed data processing and machine learning.
- SQL: Solid understanding of SQL for data querying and manipulation.
- GCS: Experience with GCS (Google Cloud Storage) for storing and managing data in the cloud.
- GitHub: Familiarity with GitHub for version control and collaborative development.
- CI/CD: Understanding of CI/CD (Continuous Integration/Continuous Deployment) principles and practices.
- Dynatrace: Experience with Dynatrace for application performance monitoring.
- Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret data and draw meaningful conclusions.
- Software Engineering: Solid foundation in Software Engineering principles and best practices.
- Design Practices: Knowledge of software design patterns and principles.
- Documentation: Ability to create clear and concise technical documentation.
- DevOps: Understanding of DevOps methodologies and practices.
- Pair Programming: Experience with Pair Programming techniques for collaborative code development.
- TDD: Familiarity with TDD (Test-Driven Development) methodologies.
- Agile: Experience working within an Agile development environment.
- Education: Bachelor's Degree required.
- Experience: 1 - 4 years of relevant experience. This level is expected to be a mid-level contributor, capable of working independently and contributing to team goals.
What We Offer
Salary:
