ML Ops engineer

Posted 3 Days Ago
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Gland, Vaud
Junior
Fintech • Software • Financial Services
The Role
As an ML Ops Engineer, you will deploy models, automate CI/CD pipelines, monitor performance, and establish best practices for ML Ops in collaboration with data scientists.
Summary Generated by Built In

Company Description

Building the bank of tomorrow takes more than skills. 

It means combining our differences to imagine, discuss, code, develop, test, learn… and celebrate every step together. Share our vibes? Join Swissquote to unleash your potential.

We are the Swiss Leader in Online Banking and we provide trading, investing and banking services to +500’000 clients, through our performant and secured digital platforms.

Our +1000 employees work in a flexible way, without dress code and in multicultural teams. 
By having a huge impact on the industry, they are growing their skills portfolio and boosting their career in a fast-pace environment

We are all in at Swissquote. As an equal opportunity employer, we welcome candidates from all backgrounds, experiences and perspectives to join our team and contribute to our shared success.

Are you all in? Don’t be shy, apply!

Job Description

We are looking for a versatile ML Ops Engineer who is ready to take on the exciting challenge of establishing ML Ops practices within our organization. As the first dedicated ML Ops Engineer in our team, you will play a crucial role in taking over models from data scientists and deploying them to robust and scalable production environments. You will ensure that our models not only perform well but are also maintained efficiently, enabling continuous improvement and business impact. 

 

Key Responsibilities 

  • End-to-End Model Deployment: Collaborate closely with data scientists and ML engineers to take over models and deploy them into production environments. 
  • Future infrastructure design: Bridge with the IT department to define requirements for the present and future infrastructure. 
  • Pipeline Automation: Develop and maintain CI/CD pipelines tailored for ML workflows, automating model versioning, testing, and deployment. 
  • Monitoring and Maintenance: Implement monitoring systems to track model performance, data drift, and system health, ensuring proactive maintenance and scalability. 
  • Standardization and Best Practices: Establish ML Ops best practices, setting the foundation for future growth and scalability. 

Qualifications

  • Educational Background: Master’s degree in Computer Science, Engineering or a related quantitative field. 
  • Experience: 
  • Proven experience of at least 2 years as an ML Ops Engineer or in a similar role, ideally in dynamic and growing teams. 
  • Experience working closely with data scientists to transition models and genAI applications from development to production. 
  • Technical Skills: 
  • Strong programming skills in Python, with knowledge of Java being a plus. 
  • Proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn). 
  • Experience with generative AI models, including leveraging proprietary APIs  and deploying on-site RAG systems. 
  • Strong experience with cloud platforms. 
  • Proficiency in CI/CD tools (GitLab CI or similar). 
  • Expertise in containerization and orchestration (Docker, Kubernetes). 
  • Experience with data pipeline orchestration tools (e.g., Airflow) is a plus. 
  • Familiarity with data streaming and monitoring tools like Kafka and Elasticsearch is a plus. 
  • Soft Skills: 
  • High degree of autonomy and proactive behavior  
  • Versatility and adaptability to take on new challenges in a fast-growing environment. 
  • Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams. 
  • Problem-solving mindset with a proactive and self-starter attitude. 

Top Skills

Airflow
Docker
Elasticsearch
Gitlab Ci
Java
Kafka
Kubernetes
Python
PyTorch
Scikit-Learn
TensorFlow
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The Company
HQ: Gland
1,306 Employees
On-site Workplace

What We Do

We are Switzerland’s leading bank in online financial services and offer our clients innovative and state-of-the-art solutions to meet their investment needs.

Headquartered in Geneva, Switzerland, we have additional offices in Zurich, Luxembourg, London, Cyprus, Dubai, Hong Kong, Malta, Singapore, and Bucharest.

Swissquote Group Holding Ltd has been listed on the SIX Swiss Exchange (symbol: SQN) since May 2000 and is regulated by the Swiss Financial Market Supervisory Authority (FINMA).

As well as various online trading products - including stocks, bonds, funds derivative products, and cryptocurrencies – Swissquote also provides Forex, Robo-Advisory, and Mortgages solutions.

Today, we are proud to deliver our services to + 500’000 clients with access to more than 60 stock exchanges worldwide and can trade over 3 million products through performant and secure platforms.

Swissquote is the marketing brand for the activities of Swissquote Bank Ltd (Switzerland) regulated by FINMA, Swissquote Bank Europe SA (Luxembourg) regulated by the CSSF, Swissquote Bank Ltd (UK) regulated by the FCA, Swissquote Financial Services (Malta) Ltd regulated by the MFSA, Swissquote MEA Ltd. (UAE) regulated by the DFSA, Swissquote Pte Ltd (Singapore) regulated by the MAS, Swissquote Asia Limited (Hong Kong) licensed by the Hong Kong SFC.

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