Senior Machine Learning Engineer - Computer Vision

Placements24; Gqeberha; Hybrid; ZAR 1,000,000 - 1,650,000; Full time

Benefits offered by this job

Stock option plan

Health, dental, and vision insurance

401k matching program

Paid time off

Online courses, conferences, and local

Job summary

Placements24 is seeking a Senior Machine Learning Engineer specialized in Computer Vision to design, train, and deploy cutting-edge CV models in a fully remote role. You will work with a cross-functional team to implement robust ML pipelines, optimize architectures, and stay current with the latest CV research.

Strong Python and cloud skills are required. You will mentor engineers, contribute to MLOps practices, and collaborate across time zones to deliver scalable AI solutions that interpret

Qualifications

• Master's or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or a related quantitative field with a focus on Machine Learning or Computer Vision.
• Minimum of 5 years of professional experience in machine learning engineering, with a significant focus on computer vision.
• Proven experience developing and deploying production-level computer vision models.
• Strong proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Solid understanding of classical computer vision techniques and algorithms.
• Experience with data processing, feature engineering, and model evaluation for image and video data.
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, essential for effective remote teamwork.
• Experience with MLOps and CI/CD for ML pipelines is a plus.

Responsibilities

• Design, develop, train, and deploy advanced machine learning models for computer vision tasks (e.g., object detection, image segmentation, facial recognition, image generation).
• Implement and optimize deep learning architectures using frameworks like TensorFlow, PyTorch, or Keras.
• Develop data augmentation strategies and preprocessing pipelines for large image and video datasets.
• Collaborate with software engineers to integrate ML models into production systems and applications.
• Conduct rigorous experimentation and evaluation of model performance, ensuring robustness and scalability.

Skills

Python

TensorFlow

PyTorch

Computer Vision

ML Engineering

Remote collaboration

MLOps

Education

Master's or PhD in Computer Science / Electrical Engineering / AI or related field

Tools

Docker

Kubernetes

AWS

GCP

Azure

Job description

About the Role

Our client, a forward-thinking technology company, is seeking an accomplished Senior Machine Learning Engineer with a specialization in Computer Vision . This fully remote position allows you to work from anywhere, contributing to groundbreaking AI projects from your own environment. You will be responsible for designing, developing, and deploying cutting-edge computer vision models and systems that drive innovation across various applications. This role demands a deep understanding of machine learning algorithms, deep learning frameworks, and the practical application of computer vision techniques. You will collaborate with a talented team of engineers and data scientists to tackle complex challenges and deliver scalable, high-performance solutions. We are looking for a self-motivated individual who excels in a remote setting and is passionate about pushing the boundaries of artificial intelligence. This is a unique opportunity to make a significant impact on the future of AI technology, working on challenging problems with a global perspective. Your expertise in computer vision will be instrumental in developing intelligent systems that can 'see' and interpret the world.

Key Responsibilities

• Design, develop, train, and deploy advanced machine learning models for computer vision tasks (e.g., object detection, image segmentation, facial recognition, image generation).
• Implement and optimize deep learning architectures using frameworks like TensorFlow, PyTorch, or Keras.
• Develop data augmentation strategies and preprocessing pipelines for large image and video datasets.
• Collaborate with software engineers to integrate ML models into production systems and applications.
• Conduct rigorous experimentation and evaluation of model performance, ensuring robustness and scalability.
• Stay abreast of the latest research and advancements in machine learning and computer vision.
• Contribute to the overall ML infrastructure and MLOps practices.
• Communicate complex technical concepts and findings to both technical and non-technical audiences.
• Mentor junior engineers and contribute to a culture of technical excellence.

Requirements

• Master's degree or Ph.D. in Computer Science, Electrical Engineering, Artificial Intelligence, or a related quantitative field with a focus on Machine Learning or Computer Vision.
• Minimum of 5 years of professional experience in machine learning engineering, with a significant focus on computer vision.
• Proven experience developing and deploying production-level computer vision models.
• Strong proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Solid understanding of classical computer vision techniques and algorithms.
• Experience with data processing, feature engineering, and model evaluation for image and video data.
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, essential for effective remote teamwork.
• Experience with MLOps and CI/CD for ML pipelines is a plus.

Benefits

• Our client offers a highly competitive salary and an attractive stock option plan.
• Comprehensive health, dental, and vision insurance are provided.
• We offer a generous 401k matching program and ample paid time off.
• Continuous learning is encouraged through access to online courses, industry conferences, and internal workshops.
• As a fully remote role, you have the flexibility to work from your preferred location, supported by a technology stipend to ensure a productive home office setup.