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Open nowPosted 38 hours agoWe saw it 34 min after it went up

Associate Machine Learning Engineer

ImagineArt21 open roles

Where
Islamabad
Work mode
On site
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Your applicationOpen nowAssociate Machine Learning EngineerImagineArt · Islamabad
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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. ImagineArt postings stay open a median of 77 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 38 hours ago

ImagineArt median: 77 days open

The posting

JOB TITLE: ASSOCIATE MACHINE LEARNING ENGINEER

Department: Engineering / AI

Location: On-Site, H-12, NSTP, Islamabad

ABOUT IMAGINEART

We're redefining how the world creates and designs.

ImagineArt is one of the fastest-growing GenAI companies in the world. We've scaled faster than most funded startups, with zero outside funding.

- 100M+ social impressions

- Built and shipped our own image generation model, now ranked #3 globally for photorealism

No funding. No shortcuts. Just a sharp, driven team building one of the strongest GenAI products in the world, and we're just getting started.

If you want to build something that truly matters, work with exceptionally smart people, and grow at a pace most companies never experience, ImagineArt is the place.

ABOUT THE ROLE

We are looking for an Associate Machine Learning Engineer who is passionate about building intelligent systems and working with modern machine learning technologies.

You will work alongside experienced ML engineers and researchers to develop, experiment with, optimize, and deploy machine learning models powering our AI products.

This role is ideal for someone with a strong foundation in machine learning, good programming skills, and a genuine interest in Generative AI, deep learning, and large-scale AI systems.

You won't just be working with existing models or running notebooks. You'll get hands-on experience building actual ML pipelines, experimenting with model architectures, improving inference performance, and taking ML solutions from experimentation to production.

WHAT YOU'LL DO

Machine Learning & Model Development

- Develop, train, evaluate, and improve machine learning models for real-world applications.

- Work with deep learning architectures and modern ML frameworks.

- Assist in implementing and experimenting with neural networks, transformers, and generative models.

- Perform data preprocessing, feature engineering, model evaluation, and error analysis.

- Experiment with different model architectures, training configurations, and hyperparameters.

Generative AI & Deep Learning

- Explore and work with modern Generative AI technologies, including diffusion models, transformers, and LLMs.

- Understand and experiment with architectures behind image, video, and other generative AI systems.

- Work with pretrained models and adapt them for specific product requirements.

- Explore techniques such as fine-tuning, transfer learning, LoRA, and other model optimization approaches.

- Stay updated with recent ML research and identify techniques that can improve our products.

ML Engineering & Deployment

- Build and maintain ML training and inference pipelines.

- Work with PyTorch and other machine learning frameworks to implement and optimize models.

- Assist in deploying models into production environments.

- Optimize inference latency, GPU utilization, and memory consumption.

- Collaborate with backend engineers to integrate ML models into scalable production systems.

- Write clean, modular, and maintainable Python code.

Research & Experimentation

- Read and understand relevant research papers and translate useful ideas into working implementations.

- Run experiments, analyze results, and document findings.

- Benchmark models against performance, quality, and efficiency metrics.

- Identify opportunities to improve existing models and ML workflows.

WHAT WE'RE LOOKING FOR

- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Must Have

- 0–2 years of experience in Machine Learning, Deep Learning, or relevant practical projects. Must Have

- Strong programming skills in Python. Must Have

- Good understanding of fundamental Machine Learning concepts, including supervised and unsupervised learning, model evaluation, and optimization. Must Have

- Hands-on experience with PyTorch or TensorFlow. Must Have

- Understanding of neural networks, backpropagation, gradient descent, and common deep learning architectures. Must Have

- Familiarity with NumPy, Pandas, and Scikit-learn. Must Have

- Understanding of CNNs, Transformers, or other deep learning architectures. Must Have

- Experience implementing ML projects beyond basic tutorials or coursework. Must Have

- Familiarity with Git, Linux, and basic software development practices. Good to Have

- Exposure to Generative AI, LLMs, diffusion models, or computer vision. Good to Have

- Familiarity with Hugging Face, pretrained models, and model fine-tuning. Good to Have

- Understanding of CUDA, GPU computing, or model inference optimization. Good to Have

- Experience reading and implementing research papers. Good to Have

- Strong problem-solving skills and willingness to experiment, learn, and build.

WHY JOIN IMAGINEART

- Work on innovative AI products used by creators around the world.

- Get hands-on exposure to real-world Generative AI systems and production ML infrastructure.

- Learn directly from experienced engineers working on challenging AI problems.

- Work with modern GPUs, ML frameworks, and cutting-edge AI technologies.

- Take ownership of meaningful projects and see your work impact millions of users.

- Grow in an environment that encourages experimentation, research, and engineering excellence.

COMPANY CULTURE

- Impact: Build and improve AI products that are shaping the future of creativity.

- Team: Work alongside a passionate, technically strong, and ambitious engineering team.

- Growth: Learn rapidly, experiment with new technologies, and take ownership of challenging problems.

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