Jobs
Job Description:
DXC Technology is committed to building diverse, inclusive teams. We welcome applications from all backgrounds and particularly encourage interest from women, underrepresented groups, and neurodivergent candidates. We offer reasonable adjustments throughout the hiring process and are dedicated to creating a supportive, accessible environment for everyone.
Machine Learning Ops Engineer
Location: Erskine, Newcastle, Farnborough or London
Candidates must be eligible for clearance
Are you passionate about bringing machine learning solutions into real-world production environments? Do you enjoy collaborating with others to build scalable, reliable systems? We are looking for a Machine Learning Ops Engineer to join our growing team. This role is ideal for someone who enjoys solving complex problems, working cross-functionally, and continuously developing their technical expertise in a supportive environment. If you don’t meet every single requirement listed below, we still encourage you to apply. We value potential, curiosity, and a willingness to learn.
Key Responsibilities
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Deploying, monitoring, and scaling machine learning models in production.
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Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products.
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Supporting the full ML lifecycle, from experimentation to deployment and optimisation.
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Applying best practices in data engineering and contributing to architectural decisions.
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Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency.
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Contributing to a culture of knowledge-sharing and continuous improvement.
Key Skills & Experience
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Strong Python skills and familiarity with ML libraries such as Pandas, Num Py, and scikit-learn.
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Experience with frameworks such as Tensor Flow, Keras, or Py Torch.
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Exposure to gradient boosting tools such as XGBoost, LightGBM, or Cat Boost.
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Experience with model deployment tools (e.g., ONNX, TensorRT, Tensor Flow Serving, Torch Serve).
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Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines.
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Experience working with distributed data processing (e.g., Py Spark) and SQL.
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Understanding of software engineering best practices, including version control (Git).
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Knowledge of CI/CD principles in ML environments.
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Experience with cloud-native ML platforms is advantageous.
Why Join Us
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Be part of a cutting-edge AI community driving digital transformation across the UK&I.
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Work at the intersection of business innovation and emerging AI technologies.
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Opportunity to shape the future of AI adoption within some of the UK’s most impactful industries.
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Collaborative, forward-thinking environment with continuous learning and development opportunities.
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here**.**
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About Luxoft (DXC)

Luxoft (DXC)
AcquiredLuxoft is a digital strategy and software engineering services company that was acquired by DXC Technology in 2019. The company provides software development, consulting, and digital transformation services to enterprise clients across various industries.
10,001+
Employees
Zug
Headquarters
Reviews
4.0
10 reviews
Work-life balance
3.8
Compensation
2.5
Culture
4.2
Career
3.2
Management
2.8
72%
Recommend to a friend
Pros
Flexible work hours
Supportive and encouraging team atmosphere
Good work-life balance
Cons
Non-competitive salary and compensation
Heavy workload and long hours
Poor management communication and direction
Salary Ranges
123 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analytics Specialist
1 reports
$134,443
total per year
Base
$103,418
Stock
-
Bonus
-
$134,443
$134,443
Interview experience
46 interviews
Difficulty
3.4
/ 5
Duration
14-28 weeks
Offer rate
38%
Experience
Positive 66%
Neutral 16%
Negative 18%
Interview process
1
Phone Screen
2
Technical Interview
3
System Design
4
Behavioral
5
Team Fit
Common questions
Tell me about a challenging project
System design question
Coding problem
Why this company
News & Buzz
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