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For Companies At a Glance
- Tasks: Lead the charge in enhancing our platform's computer vision capabilities through innovative ML solutions.
- Company: Join a cutting-edge tech company focused on transforming image and video translation products.
- Benefits: Enjoy flexible work options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team tackling complex challenges and driving innovation in machine learning.
- Qualifications: Expertise in computer vision and strong Python engineering skills are essential.
- Other info: Work with advanced technologies like Pytorch and AWS in a collaborative environment.
The predicted salary is between 43200 - 72000 £ per year.
Mission
As a Machine Learning Engineer, you will be at the forefront of advancing our platform’s computer vision capabilities. Leveraging your expertise in machine learning including data curation, pipeline development, and model monitoring, you will deliver high-performance solutions that power critical features for our growing client base.
The ideal candidate possesses a broad range of expertise in machine learning (data labeling, training pipeline development, and model deployment/maintenance), as well as strong engineering skills. In this role, you will tackle complex challenges across our computer vision (CV) projects and play a key part in driving innovation by contributing to our cutting-edge Image and Video Translation products.
Requirements
- Expertise in Computer Vision: experience delivering end-to-end CV projects (e.g., detection, segmentation, analysis, OCR, classification, video processing).
- Foundational ML Skills: familiarity with classical ML techniques (e.g., clustering, boosting).
- ML Lifecycle Knowledge: deep understanding of a machine learning project lifecycle.
- Python Engineering: experience developing and maintaining Python microservices and libraries.
- Ownership & Decision-Making: ability to work independently within a designated scope.
Key Responsibilities
- Data Management: Coordinate data labeling efforts and curate high-quality datasets.
- Model Development: Design, develop, and optimize ML training pipelines.
- Deployment: Prepare models for production and contribute to deployment processes.
- Monitoring & Maintenance: Oversee production models, ensuring proper performance through monitoring, fine-tuning, and troubleshooting.
Our technologies
- ML: Python, Pytorch, Weights & Biases, Label-Studio
- Databases: MongoDB, PostgreSQL, Elasticsearch
- Messaging Queue: Apache Kafka
- Cloud Provider: Amazon AWS
- Monitoring & Logging: ELK (EFK), Prometheus, Grafana
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Senior ML Engineer employer: Smartcat Platform Inc.
Contact Detail:
Smartcat Platform Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer
✨Tip Number 1
Make sure to showcase your experience with end-to-end computer vision projects. Highlight specific examples where you've successfully implemented detection, segmentation, or classification tasks, as this will resonate well with our focus on advancing CV capabilities.
✨Tip Number 2
Demonstrate your understanding of the machine learning lifecycle. Be prepared to discuss how you've managed data curation, model development, and deployment processes in previous roles, as this knowledge is crucial for the position.
✨Tip Number 3
Familiarize yourself with the technologies we use, such as Python, Pytorch, and AWS. If you have experience with these tools, be ready to share specific projects where you've utilized them effectively.
✨Tip Number 4
Showcase your ability to work independently and make decisions within a designated scope. Provide examples of past projects where you took ownership and drove innovation, as this aligns with our expectations for the role.
We think you need these skills to ace Senior ML Engineer
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience with computer vision projects, including specific examples of detection, segmentation, and analysis. Detail your role in these projects to showcase your expertise.
Showcase ML Lifecycle Knowledge: Demonstrate your understanding of the machine learning project lifecycle. Discuss your experience with data curation, model development, and deployment processes to illustrate your comprehensive knowledge.
Technical Skills Emphasis: Clearly list your technical skills, especially in Python and any relevant libraries like Pytorch. Mention your familiarity with databases and cloud services, as these are crucial for the role.
Personal Projects or Contributions: If you have personal projects or contributions to open-source related to machine learning or computer vision, include them. This shows initiative and a passion for the field beyond professional experience.
How to prepare for a job interview at Smartcat Platform Inc.
✨Showcase Your Computer Vision Expertise
Be prepared to discuss your experience with end-to-end computer vision projects. Highlight specific examples of detection, segmentation, and classification tasks you've worked on, and how they contributed to the success of previous projects.
✨Demonstrate Your ML Lifecycle Knowledge
Make sure to articulate your understanding of the machine learning project lifecycle. Discuss how you manage data curation, model training, deployment, and monitoring, emphasizing any challenges you've overcome in these areas.
✨Highlight Your Python Engineering Skills
Since Python is crucial for this role, be ready to talk about your experience developing and maintaining Python microservices. Share examples of libraries you've built or contributed to, and how they improved project outcomes.
✨Exhibit Ownership and Decision-Making Abilities
Prepare to discuss instances where you've taken ownership of a project or task. Explain how you made decisions independently and the impact those decisions had on the project's success, showcasing your ability to work autonomously.
