About Wondershare
As a renowned global leader in creativity and productivity solutions, Wondershare is dedicated to making cutting-edge technology accessible to everyone, fostering efficiency and innovation. With over 100 million users across 150 countries, we provide a wide range of creative software solutions, including video editing, graphic design, and AI-powered tools. Our mission is to empower the next generation of creators, and our Canadian team plays a vital role in shaping this vision. We are now looking for a Algorithm Engineer to join our team and support the growth of our Product Innovation Center.
Responsibilities
- Design, build, and iterate on machine learning models and algorithms for ranking, recommendation, search, or related domains
- Build long- and short-term signal/feature representations from large-scale, real-time, structured and unstructured data
- Own the end-to-end ML pipeline — from algorithm design and offline evaluation to production infrastructure and online experimentation
- Design and run A/B tests and other experiments to measure and validate algorithm impact
- Analyze large datasets to identify patterns, diagnose model weaknesses, and prioritize improvements
- Collaborate with engineering, product, and data science partners to translate business objectives into well-defined ML problems
- Stay current with relevant research (e.g., deep learning, LLMs/agents, reinforcement learning) and apply state-of-the-art techniques where they add measurable value
- Identify and resolve bugs and quality issues that arise during model development and deployment
Required Qualifications
- Currently pursuing a Bachelor's or Master's or PHD degree in Computer Science, Statistics, Mathematics, or a related quantitative field (expected graduation within 1–2 years preferred)
- Solid programming skills in Python (C++ a plus), through coursework, personal projects, or prior internships
- Good foundation in data structures, algorithms, and basic computational complexity
- Coursework, project, or personal experience with an ML framework (PyTorch, TensorFlow, or similar)
- Exposure to at least one of: recommender systems, ranking, search, NLP, or computer vision (course projects or personal projects count)
- A strong sense of curiosity and initiative — comfortable proposing your own ideas, experimenting, and figuring things out independently
- Creative problem-solving mindset; excited to try novel approaches rather than just following a set playbook
Preferred Qualifications
- Personal projects, Kaggle competitions, research coursework, or publications demonstrating applied ML interest and original thinking
- Basic familiarity with large-scale data tools (Spark, or similar) — not required, a plus if you've encountered them
- Exposure to LLM/agent technologies (RAG, fine-tuning, or agent frameworks) through coursework or personal exploration
- A track record of self-directed learning or side projects that show initiative beyond coursework
What You’ll Gain
- Real ownership of a well-scoped project, with the freedom to bring your own ideas and creativity to how you solve it
- Exposure to the full ML lifecycle, including how experiments and offline/online evaluation work in production
- Regular feedback and a clear path toward a return offer / new-grad conversion for strong performers
#JoinWondershare
Wondershare’s diverse culture fosters a friendly, open-minded workplace. As a member of a dynamic, high-performing team, each Wondershare employee is driven to learn, valued for their contribution, and approaches each day excited to make an impact. With great reasons to work here, take advantage by submitting your application to join our growing team.
Wondershare is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, ancestry, place of origin, religion, family status, marital status, physical disability, mental disability, sex, age, sexual orientation, political belief, or conviction of a criminal or summary conviction offense unrelated to their employment.
Benefits:
- Casual dress
- Company events
- Discounted or free food
- On-site parking
Work Location: In person
Pay: $7,000.00-$8,000.00 per month
Benefits:
- Casual dress
- Company events
- Discounted or free food
- On-site parking
Work Location: In person
