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Data Scientist - II - (Remote - US)

Jobgether
Full-time
Remote
United States
$110,000,130,000 - $110,000,130,000 USD yearly
Data Science and Analytics
Description

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Data Scientist - II in United States.

This is a high-impact role for a data scientist with experience in computer vision and deep learning. As part of a cutting-edge AI/ML team, you’ll design and optimize models that power identity verification and fraud prevention systems. You’ll work hands-on with CNNs, transformers, and potentially multimodal LLM architectures to create models that go into production and drive real-world outcomes. You’ll also collaborate closely with engineers and senior scientists to build scalable pipelines and experiment with the latest advancements in the field. This position offers the chance to grow as a technical contributor while tackling meaningful machine learning challenges.

Accountabilities:

  • Build and refine machine learning models for computer vision use cases including image classification and object detection
  • Experiment with modern architectures like ViT, CLIP, and other transformer-based models for vision and multimodal applications
  • Contribute to full ML pipelines: preprocessing, training, tuning, evaluating, and deploying models into production environments
  • Analyze large datasets, engineer features, and conduct thorough performance evaluations
  • Write clean, production-level code and support shared ML tooling and infrastructure
  • Keep pace with the latest in academic and industry research, sharing findings and driving innovation across the team



Requirements
  • Bachelor’s degree with 2–5 years of experience, or Master’s degree with relevant academic/internship work in Computer Science or related field
  • Proficiency in Python and hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn
  • Solid background in building and deploying deep learning models (especially CNNs) and working with vision transformers (e.g., ViT, CLIP, BLIP)
  • Understanding of supervised learning, overfitting, regularization, and transfer learning
  • Familiarity with version control systems (e.g., Git) and ML ops tools for experimentation tracking and reproducibility
  • Experience with cloud platforms (AWS, GCP) and containerization tools like Docker is a plus
  • Strong collaboration and communication skills with a passion for learning and problem-solving


Benefits
  • Competitive base salary ($110,000–$130,000 USD depending on experience and location)
  • Equity packages and performance-based bonuses
  • Comprehensive health benefits including medical, dental, and vision
  • Flexible remote work arrangements across North America
  • Paid time off and generous leave policies
  • Mental wellness support and employee assistance programs
  • Professional development and learning opportunities
  • Inclusive and mission-driven work culture focused on innovation and impact

Jobgether Hiring Process Disclaimer


This job is posted on behalf of one of our partner companies. If you choose to apply, your application will go through our AI-powered 3-step screening process, where we automatically select the 5 best candidates.


Our AI thoroughly analyzes every line of your CV and LinkedIn profile to assess your fit for the role, evaluating each experience in detail. When needed, our team may also conduct a manual review to ensure only the most relevant candidates are considered.


Our process is fair, unbiased, and based solely on qualifications and relevance to the job. Only the best-matching candidates will be selected for the next round.


If you are among the top 5 candidates, you will be notified within 7 days.
If you do not receive feedback after 7 days, it means you were not selected. However, if you wish, we may consider your profile for other similar opportunities that better match your experience.


Thank you for your interest!

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