In-Demand Operations engineer (mlops) Jobs

Senior Machine Learning Operations Engineer (MLOps)
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- Full-time
- Azure
- Computer Science
- DevOps
- Work from home
- Employee assistance program
Quick Apply
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Nearmap —Barangaroo NSW
- Full-time
- Hybrid work
- Computer Science
- Engineering
- Master's degree
- Vision insurance
- Free food
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Chubb —Sydney NSW
- Full-time
- Computer Science
- Engineering
- Master's degree
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Gridsight —Remote
- $160,000 - $220,000 a year
- Full-time
- Remote
- Data analysis skills
- Cleaning
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AI DevOps Engineer
Triskele Labs —Melbourne VIC
- Full-time
- Hybrid work
- Azure
- DevOps
- Master's degree
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Data Engineer
Mineral Resources —Perth WA
- Full-time
- Azure
- AWS
- AI
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Product Owner - Artificial Intelligence
Commonwealth Bank —Sydney NSW
- Full-time
- Master's degree
- Agile
- AI
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Gridsight —Canberra ACT
- Full-time
- Doctoral degree
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Lumi —Sydney NSW
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- DevOps
- AWS
- Software development
- Parental leave
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Machine Learning Engineer / Data Scientist
The Argyle Network —Sydney NSW
- $150,000 a year
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Kogan —South Melbourne VIC
- Full-time
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Machine Learning Engineer - Capital Investment - Data & AI - Sydney
The Argyle Network —Sydney NSW
- Full-time
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Senior AI Engineer/Developer - Data and AI
Fortescue —Perth WA
- Monday to Friday
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Cloud Engineer
Macquarie University —Macquarie University NSW
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Coles Group —Hawthorn East VIC
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Amazon Web Services Australia Pty Ltd —Perth WA
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Intelligen Group —Sydney NSW
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Senior Machine Learning Operations Engineer (MLOps)

Easygo -
Melbourne VIC

Quick Apply

Job Details

Full-time

Benefits

Happy hour
Work from home
Employee assistance program
Paid volunteer leave

Qualifications

CI/CD
Cloud infrastructure
Azure
Computer Science
Big data
DevOps
Engineering
Google Cloud Platform
AWS
Docker
Bachelor's degree
Terrafrom
Scripting
Security

Full Job Description

Passionate about building and deploying Machine Learning pipelines at scale to drive business value? Join our growing Data Science Team as our first Senior Machine Learning Operations (MLOps) Engineer!

What's in it for you?

As a Senior MLOps Engineer, you will work within our collaborative Data Science team to help deliver and accelerate multiple machine learning projects across our organisation.

Your role with us:

In your role with us, you will enhance our machine learning operations (MLOps), delivering: robust, scalable AWS cloud infrastructure and automation solutions, that empower our data science team. You will get the opportunity to work with petabyte-scale data across our global platforms, directly impacting millions of users.

Who are we?

At Easygo we proudly stand as a prominent service provider to a powerhouse of brands within the entertainment industry, including Stake.com, Kick.com and Twist Gaming.

Stake is the world's largest crypto casino, and leads the industry with a seamless online casino and sportsbook experience.

Level up your online entertainment with Kick.com, the vibrant live-streaming platform, which connects millions of gamers and content creators worldwide.

All alongside the innovative game design studio, Twist Gaming, which takes creativity to new heights by crafting cutting-edge and captivating games.

Our commitment to placing our clients and their communities' entertainment at the forefront of everything we do, has solidified us as the ultimate online service provider for entertainment companies.

Headquartered in the beautiful city of Melbourne, our growth has been remarkable. From humble beginnings to a thriving workforce of 700+, we've expanded not only in numbers but in ambition. There really is something for everyone here, whether you work in Tech, Marketing, Operations, Mathematics or Design, we are sure to have something for everyone.

Click play, on your career today!

What you will do:

Lead the design, implementation, and maintenance of end-to-end ML infrastructure and automation solutions, from: development, to deployment and production monitoring.
Drive cloud infrastructure and architectural decisions supporting large-scale ML workloads, leveraging Infrastructure as Code (IaC), particularly using Terraform.
Implement and maintain CI/CD pipelines, ensuring efficient model integration, deployment, and continuous delivery.
Build and optimise monitoring, alerting and logging to ensure model reliability, performance and compliance.
Collaborate closely with data scientists and stakeholders to identify infrastructure needs, streamline workflows, and effectively communicate complex technical concepts.
Provide mentorship and technical guidance to junior MLOps engineers and data scientists to promote best practices in ML infrastructure.

What you will bring:

Essential experience

5+ years of experience in MLOps, DevOps, Data Engineering and/or cloud infrastructure roles, preferably supporting data science or Machine Learning teams.
Bachelor's degree in Computer Science, Engineering, or a related technical field.
Expert proficiency in cloud infrastructure management using Terraform.
Deep hands-on experience with major cloud platforms (AWS, Azure or GCP).
Strong experience in building and maintaining CI/CD pipelines specifically for ML workloads.
Proficiency with containerisation technologies (Docker, Kubernetes).
Advanced proficiency in Python and scripting for infrastructure automation.

Bonus points if you also have:

Experience within iGaming.
Experience working with large volumes of data, preferably at petabyte-scale.
Extensive experience with distributed computing and big data technologies (e.g. Spark, Hadoop).
Familiarity with monitoring and observability platforms.
Knowledge of data security, governance, and compliance practices relevant to ML operations.

Some of the perks of joining us:

Access to over 9,000 courses across our Learning and Development Platform.
EAP access for you and your family.
Be rewarded with lucrative annual bonuses.
Give back with a paid volunteer day.
Fuel your day with daily breakfast and open pantries brimming with unlimited snacks and refreshments, all on the house.
Break up the week with on site remedial massage Wednesdays.
In house full-time barista's providing you your daily coffee needs.
Weekly team lunches and happy hour in the office from 4pm on Fridays.
Enjoy a bustling office with the option for up to 2 days work from home per week.
Fun office environment with F1 simulators, table tennis and all your favourite gaming consoles.

We believe that the unique contributions of everyone at Easygo are the driver of our success. To make sure that our products and culture continue to incorporate everyone's perspectives and experience we never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. We are passionate about providing a workplace that encourages great participation and an equal playing field, where merit and accomplishment are the only criteria for success.

Quick Apply

Refine Your Search

operations engineer (mlops) jobs

Senior Machine Learning Operations Engineer (MLOps)

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