Machine Learning Engineer
1 miesiąc temu
At PAYBACK, we're on a mission to revolutionize the world of loyalty programs. As a Machine Learning Engineer, you'll be part of our cutting-edge team that's pushing the boundaries of cloud-native software development. Your expertise in Java, Scala, and Python will help us build scalable and robust software solutions that drive real-time data processing and machine learning model training.
We're looking for a talented engineer who can work effectively in a collaborative team environment, with a passion for modern cloud-native software development, learning new technologies, and professional growth. If you're up for the challenge, join us in shaping the future of PAYBACK's tech stack.
Key Responsibilities:
- Design and implement pipelines for data preprocessing, feature engineering, and machine learning model training.
- Work with cross-functional teams to translate business needs into data-intensive, highly scalable machine intelligent solutions.
- Stay up-to-date with the latest advancements in software engineering and machine learning, and apply modern techniques and design patterns to improve our tech stack.
- Maintain and operate our current software products with a mindset of what we build, we also run.
Requirements:
- Proficiency in programming with Java, Scala, and Python.
- Solid knowledge of data structures, algorithms, and software engineering principles.
- Experience with modern real-time data streaming technologies, such as Kafka or GCP Pub/Sub.
- Understanding of SQL and noSQL databases.
- Good communication skills in English.
- Good and hands-on ability in building front ends using NextJs or Angular.
- Experience with GCP services and Terraform.
What We Offer:
- Employment contract with stable employment.
- Flexible working hours, with a start time between 8 to 10.
- Friendly atmosphere at work, with a focus on people as our most important asset.
- Benefits, including a corporate incentive program, sport card, and private medical care.
- No rigid dress code rules, with sneakers welcome.
- Training to develop hard and soft skills.
- Hybrid working model, with 2 days a week from the office and 3 days a week from home.
- Convenient location, with a new office at Rondo Daszyńskiego and remote work options.
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