MLOps Engineer

As an MLOps Engineer, you will play a critical role in developing, deploying, and maintaining machine learning systems in a production environment. Your expertise in both machine learning and operations will be essential in ensuring the seamless integration of our data science models into our software infrastructure.

To be considered for this role, you need to have previous experience with at least AWS and Python.

What will you do?‍

• Work and solve problems within AWS cloud environment.
  
• ​Develop and deploy machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn.
• ​Build robust and scalable data pipelines to collect, process, and transform large volumes of structured and unstructured data.
• ​Design, implement, and maintain infrastructure and tools for model training, testing, and deployment in a production environment.
• ​Ensure the efficient and reliable operation of machine learning systems, including monitoring, troubleshooting, and performance optimization.
• ​Implement and enforce best practices for version control, continuous integration and deployment (CI/CD), and automated testing of machine learning models.
• ​Collaborate with cross-functional teams to identify and address infrastructure and data-related challenges and optimize the overall machine learning workflow.
• ​Stay up-to-date with the latest trends and advancements in machine learning, artificial intelligence, and MLOps to drive continuous improvement and innovation.

Employee perks, benefits

• 6 extra days off: 3x localhost days and 3x sick days
  
• Referral bonus
• Benefit plus budget
  
• Multisport Card
  
• Financial contribution to Pension plan
• Education support (certificates, courses, trainings)
  
• Physiotherapist sessions once a week in the office
  
• Bonuses at every smashing life events
  
• Flexible working arrangements
  
• Transparent approach and communication
  
• Supporting your ideas

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Requirements for the employee

Candidates with education suit the position

University education (Bachelor's degree)University education (Master's degree)Postgraduate (Doctorate)

Educational Specialization

Computer Science, Data Science or a related field.

Language skills

English - Upper intermediate (B2)

Number of years of experience

3

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Personality requirements and skills

• Proven experience as an MLOps Engineer, Machine Learning Engineer, or a similar role.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and their machine learning services.
  
• Programming skills in languages such as Python or Java.
• Hands-on experience with machine learning frameworks and libraries such as Pandas, TensorFlow, PyTorch, scikit-learn, or Keras.
• Proficiency in building and managing scalable data pipelines using tools like Apache Kafka, Apache Airflow, or similar technologies.
• Solid understanding of DevOps principles and experience with CI/CD tools like Jenkins, Git, or Docker.
• Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.
• Knowledge of database systems, SQL, and big data technologies like Hadoop or Spark.
• Strong problem-solving and analytical skills with the ability to work in a fast-paced, collaborative environment.
• Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams.

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