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Job Description

We are the catalyst for the industrial world’s digital transformation.


For more than 35 years, ground breaking technologies and business models engineered and developed by Siemens Turkey R&D department contributes to the global success of Siemens


Our R&D activities focused on the fields of electrification, automation and digitalization, provides end-to-end support to our global customers on their unique digital transformation journey.


We aim to increase our strength on solution and product development with world class SW development experts, with the vision to be the digitalization partner for our global customers.


We need game changers like you, to bring the next level of smart manufacturing and infrastructure from mere concept to reality, develop tomorrow’s smart cities, and address the most critical digitalization challenges across a comprehensive range of industries.


At our company, we are looking for an  Machine Learning Engineer with a strong background in machine learning, cloud infrastructure, and model optimization. This individual will be responsible for designing, deploying, and optimizing machine learning models on AWS. The Machine Learning Engineer will collaborate closely with data scientists, DevOps teams, and software engineers to integrate ML models into production environments, ensuring scalability and reliability.


What are my responsibilities?


  • Design, develop  and deploy machine learning models on AWS to optimize processes and support operational objectives.
  • Build and maintain end-to-end ML pipelines, including data preprocessing, model training, validation, and deployment.
  • Design and manage cloud-based infrastructure using AWS native services to support machine learning workloads.
  • Monitor model performance using tools like AWS CloudWatch and SageMaker Model Monitor, ensuring model accuracy and system reliability.
  • Perform feature engineering and data preprocessing using AWS services like Glue, Athena, and SageMaker.
  • Fine-tune machine learning models to improve accuracy, scalability, and performance.

Required Qualifications:


  • B.S. and/or M.S. degree in Computer Science, Data Science, Engineering, or a related field.
  • Minimum of 5+ years of experience in machine learning engineering 
  • Knowledge in AWS cloud services such as SageMaker, Lambda, EC2, S3, and Glue or similar
  • Strong programming skills in Python, with experience using machine learning frameworks
  • Hands-on experience in model deployment, monitoring, and performance tuning 
  • Familiarity with containerization (Docker) and orchestration tools (Kubernetes, EKS).
  • Familiarity with MLOps concepts to implement .CI/CD pipelines for seamless integration of machine learning models into production.

Desired Soft Skills:


  • Strong problem-solving skills and attention to detail.
  • Excellent communication and collaboration abilities.
  • Ability to work independently in a fast-paced, agile environment.

What else do I need to know?


  • Excellent command of English is a must
  • No restrictions for travelling abroad temporarily

Desired Soft Skills:


·Excellent interpersonal communication, problem solving and analytical skills,


·Detail-oriented with a commitment to accuracy.


·Ability to work independently and manage time effectively,


·Teammate with highly collaborative, self-motivated, customer focused, positive, and upbeat attitude,


·Ability to work in a quality oriented, tidy, and organized approach,


·Eager to learn new technologies, tools, and software domain know-how,


·Develop and apply methodologies to meet customer needs,


What else do I need to know?


·Excellent command of English is a must


·No restrictions for travelling abroad temporarily.



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What we offer


  1. Speak up Culture
  2. Respectful Workplace
  3. Being part of a global work environment
  4. Attractive remuneration package
  5. Excellent recognition tools providing spot awards
  6. Learning & Development opportunities for both personal and professional growth 
  7. Leave days for parents and a variety of flexible working models that allow time off for yourself and your family 
  8. Creche allowancefor mothers
  9. Share matching programs to become a shareholder of Siemens AG
  10. Remote working and remote livingflexibility only for relevant positions
  11. Find more benefitshere

Individual benefits are adapted to meet local legal regulations, the requirements of different job profiles, locations, and individual preferences. 


 
 

 

“At Siemens we are always challenging ourselves to build a better future. We need the most innovative and diverse Digital Minds to develop tomorrow‘s reality. Find out more about the Digital world of Siemens here: www.siemens.com/careers/digitalminds”


As Siemens we believe physical barriers are not related to potential. Only the potential matters to us. Therefore, we look forward to receive applications of candidates with physical barriers and chronic illnesses. We support healthy relationships between candidates with barriers and their colleagues because we believe we can create differences together.


Siemens is dedicated to quality, equality, and valuating diversity and we welcome applications that reflect the diversity of the communities within which we work.


We are looking forward to receiving your online application. Please ensure you complete all areas of the application form to the best of you ability as we will use the data to review your suitability to the role.


Please find more information from our web site:


https://new.siemens.com/tr/tr.html


Contact
If you need more information please don't hesitate to contact us.
+90 216 459 20 00


https://new.siemens.com/tr/tr/genel/iletisim.html


insanorganizasyon.tr@siemens.com


www.instagram.com/siemensturkiye


https://m.youtube.com/user/Siemens


http://www.twitter.com/siemensturkiye


http://www.facebook.com/siemensturkiye






Job Details

Job Location
Istanbul Türkiye
Company Industry
Other Business Support Services
Company Type
Unspecified
Employment Type
Unspecified
Monthly Salary Range
Unspecified
Number of Vacancies
Unspecified

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