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Senior Data Science and Machine Learning Engineer

Nokia

London

On-site

GBP 60,000 - 100,000

Full time

9 days ago

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Job summary

Join a forward-thinking company as a Senior Data Science and Machine Learning Engineer, where your expertise in building production-ready AI/ML systems will make a significant impact. You will design and develop advanced machine learning solutions while collaborating with domain experts to translate complex business challenges into technical solutions. This role offers the opportunity to mentor others and drive best practices in ML experimentation and deployment. With a commitment to innovation and a culture of inclusion, this company empowers you to thrive and succeed in a dynamic environment.

Benefits

Continuous Learning Opportunities

Well-being Programs

Mentoring Programs

Diverse Teams

Employee Resource Groups

Qualifications

10+ years of experience in data science and machine learning.
Proven track record of deploying ML models in production environments.

Responsibilities

Design and develop advanced machine learning solutions.
Lead the development of ML platforms and tools.

Skills

Machine Learning

Data Science

Python

Statistical Modelling

MLOps

Education

Ph.D. in Computer Science

Master's in Statistics

Tools

Azure ML Services

Distributed Computing Frameworks

ML Pipelines

Senior Data Science and Machine Learning Engineer

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Senior Data Science and Machine Learning Engineer

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Job Description

We are seeking an experienced Data Science/Machine Learning Engineer with a proven track record of developing and deploying ML solutions at scale. The ideal candidate combines deep statistical knowledge with strong engineering capabilities, bringing 10+ years of experience in building production-ready AI/ML systems. This role bridges the gap between cutting-edge machine learning research and practical business applications, requiring both technical excellence and business acumen.

Design and develop advanced machine learning solutions, from concept to production deployment, addressing complex business challenges.
Build and optimize data pipelines, features, and ML infrastructure to support large-scale model training and inference.
Lead the development of ML platforms and tools that enable efficient model development, deployment, and monitoring.
Conduct sophisticated data analysis and create advanced statistical models for complex prediction and classification problems.
Implement and maintain production ML systems with focus on scalability, reliability, and performance.
Drive best practices for ML experimentation, version control, and reproducibility.
Collaborate with domain experts to translate business requirements into technical solutions.
Mentor data scientists and engineers on ML engineering best practices and system design.
Establish frameworks for model performance monitoring, drift detection, and automated retraining.
Research and implement new ML techniques to improve existing systems and solve novel problems.

Key Skills And Experience

You have:

10+ years of professional experience in data science and machine learning in production environments, with Proven track record of deploying ML models in production environments.
Ph.D. in Computer Science, Statistics, Mathematics, or related field.
Deep expertise in machine learning algorithms, statistical modelling, and optimization techniques.
Strong programming skills in Python and proficiency in ML frameworks and distributed computing frameworks, and large-scale data processing.
Expertise in ML infrastructure, including feature stores, model serving, and monitoring systems.
Strong knowledge of ML testing, validation methods, and experimental design.
Experience with MLOps practices and tools (ML pipelines, version control, containerization).
Proficiency in Azure stack and their ML services.
Deep understanding of data structures, algorithms, and software design principles.

It would be nice if you also had:

Expertise in deep learning architecture design and optimization.
Background in distributed systems and high-performance computing.
Contributions to open-source ML projects or frameworks.

About Us

Come create the technology that helps the world act together

Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.

We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work

What we offer

Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered.

Nokia is committed to inclusion and is an equal opportunity employer

Nokia has received the following recognitions for its commitment to inclusion & equality:

One of the World’s Most Ethical Companies by Ethisphere
Gender-Equality Index by Bloomberg
Workplace Pride Global Benchmark

At Nokia, we act inclusively and respect the uniqueness of people. Nokia’s employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law.

We are committed to a culture of inclusion built upon our core value of respect.

Join us and be part of a company where you will feel included and empowered to succeed.

About The Team

Nokia Technologies is licensing Nokia intellectual property, including patents, technologies, and the Nokia brand, building on Nokia’s continued innovation and decades of R&D leadership in technologies deployed in virtually all connected

devices used today. Come join us and make an impact!

Seniority level

Seniority level
Not Applicable

Employment type

Employment type
Full-time

Job function

Job function
Engineering and Information Technology
Industries
IT Services and IT Consulting and Telecommunications

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