Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer

Innova Solutions
London
11 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Job Overview

Job Title:Data & Analytics Machine Learning Ops Engineer

‍ Job Type:Contract- 12 Months

Keywords:Python, and Scala. Utilise machine learning libraries and frameworks such as PyTorch, ONNX, and XGBoost


What you'll do:


  • Study and transform data science prototypes, applying the appropriate machine learning algorithms and tools appropriate training to junior team members to ensure all components are delivered in line with Data & Analytics Standards.
  • Implement and optimise machine learning algorithms using programming languages such as Python, and Scala.
  • Utilise machine learning libraries and frameworks such as PyTorch, ONNX, and XGBoost.
  • Evaluate model performance, conduct A/B testing, and iteratively improve model accuracy and efficiency.
  • Implement machine learning models in production environments and oversee their performance using relevant metrics.
  • Implement MLOps best practiceses to improve the development, deployment and monitoring of ML models
  • Provide advice and guidance on ML best practices
  • Document machine learning processes, methodologies, and results to facilitate knowledge sharing and collaboration.
  • Stay current with the most recent developments in machine learning research, methodologies, and technologies, integrating them seamlessly into our workflow.

What you bring:

  • High-level expertise in the Python programming language including PySpark,
  • Proficiency in utilising machine learning libraries and frameworks like PyTorch, ONNX, and XGBoost.
  • Strong understanding of software testing and CI/CD principles and version control (Git, MLFlow) for automated deployment of machine learning systems
  • Familiarity with our systems (Azure cloud platform covering Azure DevOps Pipelines, Azure Functions, AzureML, Azure Databricks, CosmosDB) is desirable
  • Excellent problem-solving skills and analytical thinking.
  • Strong communication and collaboration skills.


A little about us:

Innova Solutions is a diverse and award-winning global technology services partner. We provide our clients with strategic technology, talent, and business transformation solutions, enabling them to be leaders in their field.

  1. Founded in 1998, headquartered in Atlanta (Duluth), Georgia.
  2. Employs over 50,000 professionals worldwide, with annual revenue approaching $3.0B.
  3. Delivers strategic technology and business transformation solutions globally.
  4. Operates through global delivery centers across North America, Asia, and Europe.
  5. Provides services for data center migration and workload development for cloud service providers.

Awardee of prestigious recognitions including:

  1. Women’s Choice Awards - Best Companies to Work for Women & Millennials, 2024
  2. Forbes, America’s Best Temporary Staffing and Best Professional Recruiting Firms, 2023
  3. American Best in Business, Globee Awards, Healthcare Vulnerability Technology Solutions, 2023
  4. Global Health & Pharma, Best Full Service Workforce Lifecycle Management Enterprise, 2023
  5. Received 3 SBU Leadership in Business Awards
  6. Stevie International Business Awards, Denials Remediation Healthcare Technology Solutions, 2023

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.