Unity's Vector AI team builds machine learning systems for ad targeting across billions of users ... internships. • Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow ...
Unity's Vector AI team builds machine learning systems for ad targeting across billions of users ... internships. • Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow ...
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Internship Machine Learning Startup information
What is the difference between Internship Machine Learning Startup vs Data Science Intern?
| Aspect | Internship Machine Learning Startup | Data Science Intern |
|---|---|---|
| Required Credentials | Basic programming, statistics, coursework in ML | Similar; often includes coursework in data analysis and statistics |
| Work Environment | Fast-paced startup, collaborative teams | Varies; startups or corporate settings, collaborative |
| Industry Usage | Common in tech startups focusing on AI/ML products | Widespread across tech, finance, healthcare |
| Search & Comparison Intent | Interested in ML-specific roles in startups | Looking for data analysis or data science internships |
Internship Machine Learning Startup roles focus on applying ML techniques in startup environments, often requiring programming and statistical skills. Data Science Internships may encompass broader data analysis tasks across various industries. Both roles share similar credentials and work environments, but ML internships are more specialized in machine learning applications within startups.
What are the most commonly searched types of Machine Learning Startup jobs in New York? The most popular types of Machine Learning Startup jobs in New York are:
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What job categories do people searching Internship Machine Learning Startup jobs in New York look for? The top searched job categories for Internship Machine Learning Startup jobs in New York are:
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What cities in New York are hiring for Internship Machine Learning Startup jobs? Cities in New York with the most Internship Machine Learning Startup job openings:
Full-time
Re-posted 5 days ago
Job description
Job Summary:
Unity's Vector AI team builds machine learning systems for ad targeting across billions of users. They are seeking a Machine Learning Engineer to develop next-generation recommendation systems that leverage advanced techniques such as reinforcement learning and large language models.
Responsibilities:
• Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
• Develop user understanding systems — conversion prediction, behavioral modeling, and value estimation — that operate across billions of impressions.
• Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
• Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
• Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
• Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.
Qualifications:
Required:
• PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
• Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
• Experience working with large-scale data and ML systems, whether through research or industry internships.
• Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• A track record of rigorous, high-quality research — publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
• Strong written and verbal communication skills — able to make complex ideas accessible across technical and non-technical audiences.
Preferred:
• Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
• Hands-on experience with production ML pipelines — training at scale, feature engineering, or experimentation infrastructure.
• Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
• Familiarity with agentic AI approaches — multi-step reasoning, tool use, or human-AI collaboration frameworks.
• Exposure to causal inference, uplift modeling, or A/B testing at scale.
• Genuine curiosity about applied research and the drive to see ideas through to impact.
Company:
Unity [NYSE: U] offers a suite of tools to create, market, and grow games and interactive experiences across all major platforms from mobile, PC, and console, to extended reality. Founded in 2004, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
Unity's Vector AI team builds machine learning systems for ad targeting across billions of users. They are seeking a Machine Learning Engineer to develop next-generation recommendation systems that leverage advanced techniques such as reinforcement learning and large language models.
Responsibilities:
• Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
• Develop user understanding systems — conversion prediction, behavioral modeling, and value estimation — that operate across billions of impressions.
• Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
• Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
• Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
• Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.
Qualifications:
Required:
• PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
• Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
• Experience working with large-scale data and ML systems, whether through research or industry internships.
• Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• A track record of rigorous, high-quality research — publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
• Strong written and verbal communication skills — able to make complex ideas accessible across technical and non-technical audiences.
Preferred:
• Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
• Hands-on experience with production ML pipelines — training at scale, feature engineering, or experimentation infrastructure.
• Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
• Familiarity with agentic AI approaches — multi-step reasoning, tool use, or human-AI collaboration frameworks.
• Exposure to causal inference, uplift modeling, or A/B testing at scale.
• Genuine curiosity about applied research and the drive to see ideas through to impact.
Company:
Unity [NYSE: U] offers a suite of tools to create, market, and grow games and interactive experiences across all major platforms from mobile, PC, and console, to extended reality. Founded in 2004, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.