MLOps Engineer: Scalable AI Infra & Deployment

Talenzon group

Greater London, UK

1 day ago

Apply on www.collegerecruiter.com

Prepare application

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.collegerecruiter.com

Tech stack

Artificial Intelligence Python (Programming Language) Machine Learning Machine Learning Operations

Job description

Talenzon group is seeking an MLOps Engineer to join their team in London. This role focuses on designing and maintaining MLOps infrastructure to support machine learning lifecycle management. You will build CI/CD pipelines for training, testing, and deployment of ML models, working closely with data scientists to ensure reliability and efficiency.

The ideal candidate will have strong experience with MLOps workflows, cloud platforms, and automation using Python. Join us to help scale innovative AI systems!

Requirements

The ideal candidate will have strong experience with MLOps workflows, cloud platforms, and automation using Python. Join us to help scale innovative AI systems! #J-18808-Ljbffr

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.collegerecruiter.com

Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

Explore playlists

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

3:46 min

Core terminology and audiences for interpretable artificial intelligence

Karol Przystalski · LIVE

4:25 min

Optimizing agricultural practices through automated machine learning operations

Simi Olabisi · LIVE

4:19 min

Introduction to DevOps for AI and MLOps

Aarno Aukia · LIVE

1:57 min

Evolution of machine learning algorithms and computing hardware

Alexandra Waldherr · LIVE

5:28 min

Defining MLOps and its role in production systems

Hauke Brammer · World Congress 2023

Videos

See all

Effective Machine Learning - Managing Complexity with MLOps thumbnail

World Congress 2021 • about 5 years ago

Effective Machine Learning - Managing Complexity with MLOps

Simon Stiebellehner

Introduction to Azure Machine Learning thumbnail

LIVE • over 4 years ago

Introduction to Azure Machine Learning

Jose Luis Latorre Millas

Edit Your Future: Queerverse Radical AI thumbnail

LIVE • about 2 years ago

Edit Your Future: Queerverse Radical AI

Răzvan Ion

MLOps - What’s the deal behind it? thumbnail

World Congress 2022 • about 4 years ago

MLOps - What’s the deal behind it?

Nico Axtmann

What non-automotive Machine Learning projects can learn from automotive Machine Learning projects thumbnail

World Congress 2022 • about 4 years ago

What non-automotive Machine Learning projects can learn from automotive Machine Learning projects

Jan Zawadzki

DevOps for Machine Learning thumbnail

World Congress 2021 • about 5 years ago

DevOps for Machine Learning

Hauke Brammer

Related articles

See all

MLOps – What’s the deal behind it?

Benedikt Bischof

MLOps – What’s the deal behind it?

almost 4 years ago

MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production

Benedikt Bischof

MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production

almost 4 years ago

MLOps And AI Driven Development

Benedikt Bischof

MLOps And AI Driven Development

over 4 years ago

What Are Large Language Models?

What Are Large Language Models?

almost 3 years ago

How to Become an AI Engineer

How to Become an AI Engineer

almost 3 years ago

Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production

Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production

almost 2 years ago