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Machine Learning Engineer

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Opportunity details

About this role.

AI Summary

Skylum is seeking a senior Machine Learning Engineer to develop and enhance ML models for computer vision and image processing tasks within their award-winning photo editing software. The role involves working on standard tasks like segmentation and detection, as well as advanced problems involving diffusion models, LLMs, and VLMs. Candidates should have 4+ years of ML experience, strong Python and PyTorch skills, and the ability to implement ideas from cutting-edge research. The position offers flexibility, a supportive team, and benefits like medical insurance and educational allowances. This is a remote-friendly, fast-paced role requiring independence and collaboration.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe role requires extensive experience in computer vision, generative models, and optimizing for local devices, plus the ability to read and implement research papers, indicating a high level of difficulty.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$150,000
US market range$120k–$200k
AI insightThe salary is not specified, but for a senior Machine Learning Engineer with 4+ years experience and computer vision focus, the US market median is approximately $150,000. This role likely offers a competitive total compensation package given the required expertise and the company's benefits.

Core skills

Skills and capabilities most closely associated with this opportunity.

Cover letter sample

Dear Hiring Manager,

I am excited to apply for the Machine Learning Engineer position at Skylum. With over 5 years of experience in computer vision and deep learning, I have built and deployed models for object detection, segmentation, and generative tasks. My background includes implementing architectures from recent CVPR and NeurIPS papers and optimizing models for efficient inference on edge devices using PyTorch and ONNX Runtime.

I am particularly drawn to Skylum's mission of making photo editing accessible and creative. In my previous role, I led the development of an image enhancement pipeline that improved user engagement by 20%. I am comfortable working independently, rapidly prototyping new ideas, and collaborating cross-functionally to bring products to market.

I look forward to contributing to your innovative team and would welcome the opportunity to discuss how my skills align with your needs.

Sincerely,
[Your Name]

Sample interview questions
Can you describe a challenging computer vision problem you solved from data collection to deployment?

In my previous role, I worked on real-time object detection for a mobile app. I collected and annotated a custom dataset, selected a lightweight architecture (MobileNet-SSD), and optimized it using quantization and pruning to run on hardware-constrained devices. I deployed the model using TensorFlow Lite and achieved 95% accuracy with a latency under 50ms.

How do you stay current with the latest research in computer vision and machine learning?

I regularly read papers from top conferences like CVPR, ICCV, and NeurIPS. I also implement state-of-the-art models in PyTorch to understand their strengths and weaknesses. For example, I recently reproduced a diffusion model for image inpainting and adapted it for our product.

What experience do you have with diffusion models and how would you fine-tune one for image enhancement?

I have trained and fine-tuned diffusion models for tasks like super-resolution and denoising. I use Hugging Face Diffusers and PyTorch, adjusting the noise schedule and conditioning on low-resolution inputs. I also handle large datasets by using data loaders and distributed training to speed up the process.

How do you optimize a deep learning model for inference on a local device with limited resources?

I start by profiling the model to identify bottlenecks. Then I apply techniques like quantization (FP16, INT8), pruning, and knowledge distillation. I also leverage hardware-specific runtimes like ONNX Runtime or OpenVINO. For example, I reduced a segmentation model's size by 4x with less than 1% accuracy drop using structured pruning.

Tell me about a time you had to implement a research idea without a ready-made solution. How did you approach it?

I needed to generate photorealistic image edits conditioned on text prompts. Since no off-the-shelf model existed, I combined a pre-trained VLM for text embeddings with a GAN for image synthesis. I designed experiments to test different architectures, iterated on the training pipeline, and eventually achieved compelling results that were incorporated into the product.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.

Skylum allows millions of photographers to make incredible images. Our award-winning software automates photo editing with the power of AI yet leaves all the creative control in the hands of the artist.

Join us on our mission to make photo editing enjoyable, easy, and accessible to anyone. You’ll be developing products with innovative technologies, providing value and inspiration for customers, and getting inspired in return.

Thanks to our incredible team of experts, we’ve built a collaborative space where you can constantly develop and grow in a supportive way. At the same time, we believe in the freedom to be creative. Our work schedule is flexible, and we trust you to give your best while we provide you with everything you need to make work hassle-free. Skylum is proud to be a Ukrainian company, and we stand with Ukraine not only with words but with actions. We regularly donate to various organizations to help speed up the Ukrainian victory.

Role Mission:

We are looking for a senior Machine Learning Engineer who can build and improve ML models used in our product. Most of the tasks are related to computer vision and image processing. You will work on both common tasks like segmentation, detection, and classification, as well as more complex problems involving Diffusion Models, LLMs, VLMs, and other custom tasks without ready-made solutions.

You should be able to work independently, move fast, and quickly test new ideas.

Responsibilities:

  • Build and improve ML models, mostly for computer vision tasks.
  • Handle the full ML process: collect and prepare data, train and test models, and improve them step by step.
  • Work on both standard and new types of problems.
  • Create fast prototypes and help turn successful ones into real products.
  • Work closely with other teams to bring your models into the product.

Requirements:

  • 4+ years of real-world experience with ML, including at least 2 years in computer vision.
  • Good understanding of how to build ML systems from start to finish.
  • Hands-on experience with one or more of these: object detection, segmentation, img2img, generative networks.
  • Ability to read, understand, and implement ideas from cutting-edge research papers. You stay current with top conferences (e.g., CVPR, NeurIPS, ICCV) and can turn academic innovations into practical solutions.
  • Strong skills in Python and PyTorch.
  • Experience optimizing models for efficient inference on local devices (CPU, GPU, NPU), including quantization, pruning, and runtime adaptation.
  • Able to work with and explore large datasets.
  • Comfortable working on your own and taking full responsibility for your tasks. Experience with prototyping and working in an R&D cycle.

Nice to Have

  • Experience in research (PhD, papers, or personal projects).
  • Experience training or fine-tuning foundational models (LLMs, VLMs).
  • Experience training or fine-tuning diffusion models for specific image generation or enhancement tasks.
  • Familiarity with classical image processing techniques.
  • Experience with deep learning inference frameworks like ONNX Runtime, OpenVINO, Core ML, or others.
  • Strong C++ skills, close to your Python level.
  • Enjoy building and testing product ideas quickly.

What we offer:

For personal growth:

  • A chance to work with a strong team and a unique opportunity to make substantial contributions to our award-winning photo editing tools;
  • An educational allowance to ensure that your skills stay sharp;
  • English and German classes to strengthen your capabilities and widen your knowledge.

For comfort:

  • A great environment where you’ll work with true professionals and amazing colleagues whom you’ll call friends quickly;
  • The choice of working remotely or in our office space located on Podil, equipped with everything you might need for productive and comfortable work.

For health:

  • Medical insurance;
  • Twenty-one days of paid sick leave per year;
  • Healthy fruit snacks full of vitamins to keep you energized.

For leisure:

  • Twenty-one days of paid vacation per year;
  • Fun times at our frequent team-building activities.

What to expect when you apply

  • An interview with our Talent Acquisition Specialist
  • Professional interview
  • Management interview

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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