Machine Learning Engineer Language
Machine Learning Engineer Language

Machine Learning Engineer Language

Full-Time 28800 - 48000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join our Personalization team to develop cutting-edge machine learning products and enhance customer experiences.
  • Company: Optimove is a leading marketing tech company, partnering with top brands like Sephora and Staples.
  • Benefits: Enjoy a supportive team environment, remote work options, and opportunities for rapid experimentation.
  • Why this job: Be at the forefront of machine learning, making a real impact on personalization across digital platforms.
  • Qualifications: Strong programming skills in Python, experience with SQL, and familiarity with machine learning libraries required.
  • Other info: Work with multi-modal data and state-of-the-art technologies like Large Language Models.

The predicted salary is between 28800 - 48000 £ per year.

Optimove is a global marketing tech company, recognized as a Leader by Forrester and a Challenger by Gartner. We work with some of the world\’s most exciting brands, such as Sephora, Staples, and Entain, who love our thought-provoking combination of art and science. As a Machine Learning Engineer, you will be working within our Personalization team, helping to shape and drive the development of numerous products and initiatives that allow our customers to personalise messages across all digital touchpoints. This includes working with multi-modal data such as images, text, and more, leveraging cutting-edge technologies including Large Language Models (LLMs). This is an exciting opportunity at the forefront of machine learning, helping to bring Accessible Intelligence to our customers with great scope to make a key difference across both OptiX and Optimove\’s overall platforms. We are looking for an experienced Machine Learning Engineer to work on incredibly interesting projects as we take our personalization capabilities to the next level. You will focus on developing and advancing ML/AI across our platforms, researching and investigating new machine learning applications within the company, and improving pre-existing models. Monitor production models, ensuring data quality and model performance. Develop predictive machine learning models for classification, ranking, and personalization purposes, utilizing multi-modal data including images and text. Research and investigate new machine learning applications within the company, and improve on pre-existing models. Collaborate closely with product and development teams to define and prepare new ML applications. Analyse performance and continuously improve scoring processes for hosted models. Exposure to a phenomenal array of machine learning domains, including massive-scale search, ranking, NLP, hybridization, classification, multi-modal data processing (images, text, etc.), Leveraging state-of-the-art technologies, including Large Language Models (LLMs), to enhance our products and services. Fully real-time architecture for data processing, model development, and deployment. Deploying and enhancing ML frameworks, optimizing for inference, and training/retraining cycles. Online testing for models with live data using proprietary A/B/N testing technology to rapidly determine what works (and what doesn\’t). A super-bright, supportive, and friendly machine learning team to work with in an environment where rapid experimentation is the norm. Regular time allocated to research new methods, build and test proofs-of-concept, and deploy to production instantly if effective. Strong programming skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions, including Snowflake. Understanding of personalization for various domains, including sports betting and gaming, where it might add value and what best practices look like. Professional experience in personalization and/or predictive CRM, and micro-segmentation. indicates a required field Phone * Website Do you have a work permit in the UK? * Do you require a visa sponsorship in the UK? * Your personal data will be retained by Controller as long as Controller determines it is necessary to evaluate your application for employment. Under the GDPR, you have the right to request access to your personal data, to request that your personal data be rectified or erased, and to request that processing of your personal data be restricted. You also have to right to data portability. In addition, you may lodge a complaint with an EU supervisory authority. #

Machine Learning Engineer Language employer: Optimove

At Optimove, we pride ourselves on being a leading marketing tech company that fosters a vibrant and innovative work culture. As a Machine Learning Engineer, you'll have the opportunity to collaborate with a super-bright team, engage in rapid experimentation, and contribute to cutting-edge projects that shape the future of personalisation. With a strong emphasis on employee growth, we provide regular time for research and development, ensuring you can continuously enhance your skills while making a meaningful impact on our products and services.
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Contact Detail:

Optimove Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer Language

✨Tip Number 1

Familiarise yourself with the latest advancements in machine learning, particularly in multi-modal data processing and Large Language Models (LLMs). This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.

✨Tip Number 2

Engage with the machine learning community by attending relevant meetups or webinars. Networking with professionals in the industry can provide insights into current trends and may even lead to referrals for job openings.

✨Tip Number 3

Showcase your hands-on experience with machine learning frameworks like TensorFlow or PyTorch through personal projects or contributions to open-source. Having a portfolio that highlights your skills can set you apart from other candidates.

✨Tip Number 4

Prepare to discuss specific examples of how you've improved model performance or developed predictive models in previous roles. Being able to articulate your problem-solving process will impress interviewers and show your practical expertise.

We think you need these skills to ace Machine Learning Engineer Language

Machine Learning Algorithms
Large Language Models (LLMs)
Multi-modal Data Processing
Python Programming
Data Manipulation with Pandas and NumPy
SQL for Data Querying
Git Version Control
Bash Scripting
Docker Containerization
Machine Learning Frameworks (scikit-learn, PyTorch, TensorFlow, SciPy)
Model Deployment and Monitoring
Real-time Data Processing
A/B/N Testing Methodologies
Software Engineering Principles
Clean Code Practices
Cloud Technologies (e.g., Snowflake)
Personalization Techniques
Predictive CRM and Micro-segmentation

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with multi-modal data and technologies like Large Language Models. Use specific examples of projects you've worked on that align with the job description.

Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and personalisation. Mention specific brands or projects from Optimove that excite you and explain how your skills can contribute to their goals.

Showcase Technical Skills: Clearly list your programming skills, especially in Python and SQL, as well as your experience with machine learning libraries like TensorFlow and PyTorch. Provide examples of how you've used these skills in past roles.

Highlight Collaborative Experience: Since the role involves working closely with product and development teams, include examples of successful collaborations in your application. Emphasise your ability to communicate complex technical concepts to non-technical stakeholders.

How to prepare for a job interview at Optimove

✨Showcase Your Technical Skills

Be prepared to discuss your programming skills, especially in Python, and your experience with machine learning libraries like TensorFlow and PyTorch. Bring examples of projects you've worked on that demonstrate your ability to handle multi-modal data.

✨Understand the Company’s Products

Familiarise yourself with Optimove's offerings and how they leverage machine learning for personalisation. This will help you articulate how your skills can contribute to their goals and show your genuine interest in the company.

✨Prepare for Problem-Solving Questions

Expect to face technical questions that assess your problem-solving abilities. Practice explaining your thought process clearly and concisely, as this will be crucial when discussing model development and optimisation.

✨Demonstrate Collaboration Skills

Since the role involves working closely with product and development teams, be ready to share examples of how you've successfully collaborated in the past. Highlight your communication skills and your ability to work in a team-oriented environment.

Machine Learning Engineer Language
Optimove
O
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