MLOps Engineer

Moz://a.ai is at the forefront of the AI revolution, advocating for a decentralized and open-source approach. Our ambition is to empower developers to craft AI solutions that are both scalable and trustworthy. Through innovation, collaboration, and responsible AI practices, we're shaping an AI future anchored in user agency, privacy, and transparency.

• Position: MLOps Engineer
• Location: Madrid, Lisbon, London (Temote)
• Type: Full-Time
• Expected Start Date: Q2 2024

Position Overview: 

As an MLOps Engineer, you will focus on creating and maintaining a cloud platform that simplifies the selection, evaluation, and fine-tuning of language models for various businesses. Your primary focus will be to bridge the gap between Machine Learning Engineers and Data Scientists and operations, ensuring seamless deployment, monitoring, and scaling of machine learning models Your main responsibilities will be:.

• Develop and maintain end-to-end machine learning lifecycle management, including data preparation, model training, validation, deployment, monitoring, and updating.
• Implement mechanisms for selecting and evaluating language models based on various criteria such as accuracy, efficiency, and suitability for specific business use cases. 
• Collaborate with data scientists and engineers to define evaluation metrics and benchmarks for assessing model performance.
• Implement automated model deployment pipelines, enabling data scientists to easily deploy and manage models in production environments.
• Work closely with data scientists, platform engineers, and other stakeholders to understand model requirements and facilitate smooth integration with the platform.
• Implement monitoring, logging, and alerting solutions for machine learning models in production, ensuring proactive maintenance and troubleshooting.
• Develop and maintain CI/CD pipelines for machine learning models, accelerating time-to-market and streamlining development workflows.
• Create clear and comprehensive documentation for MLOps processes, tools, and best practices.
  
  

Qualifications:

• Proven experience in MLOps or similar roles, with a focus on machine learning and AI applications.
• Proficiency in managing cloud environments (AWS is a must have, others are a big plus) and familiarity with cloud-native technologies and services.
• Demonstrable experience using MLOps frameworks, like MFlow or Kubeflow. 
• Experience with automation tools and practices, such as infrastructure-as-code, CI/CD pipelines, and automated testing. 
• Hands-on experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation) to automate the provisioning and management of resources
• Strong programming skills in languages such as Python, along with experience in shell scripting.
• Familiarity with containerization technologies (e.g., Docker) and orchestration systems (e.g., Kubernetes).
• Excellent communication skills and the ability to collaborate effectively in a fast-paced, team-oriented environment.
• Strong problem-solving abilities and a proactive approach to troubleshooting and resolving issues.

If you have any questions about this role or how you can bring your unique skills to our team, please don't hesitate to get in touch.

Why us 

We are more than just a company; we are a community of like-minded individuals driven by a shared passion for creating positive change in society through AI solutions.

1. Purpose-Driven Mission: we are a mission-driven early stage company. If you are passionate about the transformative potential of AI and committed to ensure AI solutions that are trustworthy and responsible.
2. Innovation & Impact: cutting-edge AI projects that have a real impact on people's lives.
3. Collaborative Culture: Our team is distributed across different countries, fostering a collaborative and inclusive culture where everyone's input is valued. We make sure to meet several times a year to work together in a place in the world defined in advance.
4. Remote work: We are a 100% remote team, distributed around the world. Since we do not have offices in all locations (we partner with an Employer of Record). 

We are committed to building a diverse and inclusive team. We encourage applications from individuals of all backgrounds, beliefs, and identities.

Compensation, Benefits and Perks

• Premium package featuring core benefits tailored to your country of residence encompassing essential services such as health insurance and retirement plans (check our comprehensive list of core benefits per location) 
• 25 per year of Paid Time-off
• Generous performance-based bonus plans to all regular employees 
• One-time home office stipend of 1,000 USD
• Annual professional development budget
• Annual well-being stipend of 3,500 USD