Sr. Computer Vision & AI Engineer

PixoAnalytics
London
4 days ago
Create job alert

Key Responsibilities

  • Design & Implement Computer Vision Solutions: Develop and optimize end-to-end computer vision pipelines using advanced deep learning techniques.
  • LLMs-VLMs: Have awareness about the latest technologies in the field of LLMs and VLMs.  
  • Model Development & Deployment: Build, train, and deploy deep learning models (e.g., object detection, image segmentation, classification) using frameworks like PyTorch and TensorFlow.
  • Data Pipeline & Infrastructure: Work closely with data engineers to ensure efficient data preprocessing, augmentation, and real-time inference pipelines.
  • Docker & REST APIs: Containerize applications for scalable deployments and create robust RESTful APIs for seamless integration with other services.
  • UI Development (PyQt): Develop or integrate user interfaces for internal tools or customer-facing applications.
  • Model Monitoring & Experiment Tracking: Leverage tools like Weights & Biases (wandb) or MLflow to track experiments, monitor model performance, and ensure continuous improvement.
  • Performance Optimization: Conduct performance tuning and hardware optimization (GPU/CPU) to achieve high throughput and low latency.
  • Collaboration & Mentorship: Work in cross-functional teams (Product, Data, DevOps) and mentor junior developers on best practices and new technologies.



Find out more about this role by reading the information below, then apply to be considered.

Required Qualifications

  • 5+ years of hands-on experience in Computer Vision and Deep Learning.
  • Fluency in Python; additional programming languages (C++, Java, etc.) are a plus.
  • Expertise in Deep Learning Frameworks: PyTorch and TensorFlow.
  • Proficiency with Docker for containerization and microservices.
  • Experience with RESTful API design and implementation.
  • Knowledge of PyQt (or similar frameworks) for desktop UI development.
  • Familiarity with Model Monitoring & Experiment Tracking (Weights & Biases, MLflow, etc.).
  • Strong background in linear algebra, calculus, and probability/statistics as they relate to ML.
  • Excellent problem-solving and debugging skills.
  • Bachelor’s/Master’s/PhD in Computer Science, Electrical Engineering, or a related field (or equivalent work experience).


Preferred Skills & Nice-to-Haves

  • Experience with DevOps practices (CI/CD, Kubernetes).
  • Familiarity with Cloud Platforms (AWS, Azure, GCP) for model deployment and scaling.
  • Understanding of Edge Computing and on-device model optimization (TensorRT, ONNX).
  • Knowledge of NVIDIA CUDA for GPU acceleration.
  • WANDB and MLflow for training monitoring.
  • Contributions to open-source computer vision or deep learning projects. 


What We Offer

  • Competitive Compensation
  • Flexible Work Arrangements (Remote) and a positive work-life balance.
  • Growth Opportunities: A chance to lead cutting-edge projects and mentor junior developers.
  • Collaborative Culture: Work alongside passionate professionals in an environment that values innovation and continuous learning.



Related Jobs

View all jobs

Senior Director Artificial Intelligence/Machine Learning (Hiring Immediately)

Sr Data Scientist - voice (Hiring Immediately)

Sr Data Scientist

Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM (Hiring Immediately)

Senior Machine Learning Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Rural-Remote AI Jobs: A Breath of Fresh Air in the UK Tech Scene

A New Horizon for AI Professionals For years, conversations around tech careers in the UK have hinged on a central theme: to succeed in artificial intelligence (AI), you must be in or around London (or other big metropolitan areas like Manchester, Bristol, or Edinburgh). But times are changing. Technological leaps and the rise of flexible working are paving the way for AI professionals to live and work well beyond the capital. From the rugged coastlines of Cornwall and Pembrokeshire to the rolling hills of the Yorkshire Dales, we’re witnessing an exciting trend of AI remote countryside roles that allow you to work at the forefront of tech innovation—all while enjoying the tranquillity of rural or seaside living. At ArtificialIntelligenceJobs.co.uk, we’re seeing a marked increase in job postings and applications for these sorts of positions. A growing segment of job seekers is actively searching for “tech jobs by the sea” or “AI remote countryside,” driven by a desire for better work-life balance, lower living costs, and a healthier lifestyle. And it’s not just employees who stand to benefit; employers eager to attract top-tier AI talent are discovering that offering remote or flexible roles widens their candidate pool and enhances diversity. If you’re enticed by the idea of logging off from a day of coding neural networks and taking a stroll along a coastal path—or stepping outside your converted barn in Northumberland to soak in some fresh country air—this article is for you. Below, we’ll explore the benefits and challenges of rural-remote AI jobs, the specific roles best suited for remote work, and how to position yourself for success in this rapidly evolving sector.

When Qubits Fuel Neural Networks: The Emerging Frontier of Quantum-Enhanced AI

Artificial Intelligence (AI) has soared to unimaginable heights over the last few years, revolutionising sectors ranging from healthcare and finance to logistics and entertainment. But while deep learning models have grown more sophisticated and powerful, they remain tied to the limitations of classical computing systems. Enter quantum computing, a burgeoning field that leverages qubits—quantum bits—to achieve processing speeds that could leave even today’s most advanced supercomputers in the dust. What if we combined these two forces? Quantum-enhanced AI aims to integrate quantum hardware and algorithms into AI workflows, potentially unlocking efficiencies and capabilities that are currently out of reach. Although this domain is still in its infancy, experts predict it could reshape entire industries in the not-so-distant future. For professionals in AI, this is more than just an interesting development; it’s a pivotal shift that could spawn new roles, research areas, and opportunities. In this thought-leadership piece, we will: Outline the basics of quantum computing and why it matters to AI. Examine how quantum resources might supercharge neural networks. Highlight the career paths at the intersection of quantum and machine learning. Discuss the long-term outlook and what it means for AI professionals looking to stay ahead. Whether you’re already immersed in AI or just beginning to explore its potential, strap in—this new frontier promises a radical transformation.

AI Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Over the last decade, the United Kingdom has firmly established itself as one of Europe’s most significant technology hubs. Thanks to a vibrant ecosystem of venture capital, government-backed initiatives, and a wealth of academic talent, the UK has become especially fertile ground for artificial intelligence (AI) innovation. This growth is not just evident in established tech giants—new start-ups are emerging every quarter with fresh ideas, ground-breaking technologies, and a drive to solve real-world problems. In this Q3 2025 Investment Tracker, we take a comprehensive look at the latest AI start-ups in the UK that have successfully secured funding. Beyond celebrating these companies’ milestones, we’ll explore how these recent investments translate into exciting new job opportunities for AI professionals. Whether you’re an experienced machine learning engineer, a data scientist, or simply hoping to break into the AI sector, this roundup will give you insights into the most in-demand roles, the skills you need to stand out, and how you can capitalise on the current AI hiring boom.