MLOps Manager

Company Description

Are you looking for an opportunity to jump-start your career in a thriving tech industry? Join us at Blend a company to grow our business and execute our mission to help organizations leverage data and technology to make better decisions. With over 10 years of experience in the field of big data, top US customers such as Mastercard, Tripadvisor, and Roku choose us to develop innovative products.

Job Description

What is this position about? 

You will be a part of a dynamic, high-performance team at a renowned global hospitality company, well known for its world-class guest experiences and services. In this role, you will work closely with machine learning engineers, data scientists, and cloud architects to support the deployment and operationalization of machine learning models. Your focus will be on developing and maintaining MLOps pipelines, ensuring seamless integration of machine learning applications into the production environment. 

The position involves managing key cloud infrastructure and optimizing machine learning operations to enhance the overall data ecosystem of the organization. You’ll be responsible for deploying and managing robust solutions using modern cloud technologies and collaborating with cross-functional teams to ensure smooth delivery of projects. 

What will I be doing? 

• Developing, maintaining, and optimizing MLOps pipelines for real-time predictive model deployment. 

• Building data pipelines and CI/CD pipelines that align with industry standards for machine learning operations. 

• Working with AWS services such as Lambda, SageMaker, Glue, and CloudFormation to support and scale machine learning models. 

• Collaborating with teams using Agile development methodologies to ensure efficient and timely project delivery. 

• Supporting downstream system integrations, troubleshooting issues as needed. 

Qualifications

What expertise do I need? 

• Hands-on experience with AWS services, particularly in Lambda, Glue, and SageMaker. 

• Proficiency in PySpark for developing data pipelines. 

• Solid experience with CI/CD processes and infrastructure as code (CloudFormation or similar). 

• Ability to deploy real-time predictive endpoints into production environments. 

• Experience working in an Agile development environment. 

• Experience with real-time data processing and deploying predictive models in production. 

• Familiarity with MLOps tools and frameworks to streamline operations. 

What about languages? 

Strong written and verbal English communication skills are essential to effectively collaborate with global teams. 

How much experience must I have? 

We are looking for candidates with 8+ years of experience in data engineering, MLOps, or a related field, with MLOps teams and projects. 

Additional Information

Our perks and benefits:

🍔Every day lunches! (headquarters)

• Vegetarian, vegan, gluten and sugar free options.

• Gourmet meals every Friday with our on-site chef!

⚖️ Flexible working options to help you strike the right balance.

👨🏽‍💻 All the equipment you need to harness your talent (Macbook and accessories).

☕Snacks and beverages available everyday (headquarters).

🎮After office events, football, tennis and game nights (headquarters).

• Everyone is welcome to join our football league every Wednesday’s and Friday’s.

• Challenge your teammates to a pool game and win the office’s trophy!

• Tennis courts available for friendly matches.

• You are not a sports person? Don’t worry, we also have chess championships, game and music nights for you to join!

📚 Learning opportunities:

• AWS Certifications (we are AWS Partners).

• Study plans, courses and other certifications.

• English Lessons.

• Learn from your teammates on our Tech Tuesdays!

👩‍🏫 Mentoring and Development opportunities to shape your career path.

🎁 Anniversary and birthday gifts.

🏡 Great location and even greater teammates!

 So what are the next steps?

Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!

Cheers!