Data Scientist - Computer Vision
关于美国，ARRISE 为 iGaming 行业的服务提供和卓越设定了基准。在其客户成功中发挥关键作用，其中包括世界上最大的网上场所以其尖端产品依赖的 Pragmatic Play,ARRISe 帮助全球数百万玩家获得非凡的游戏体验。我们拥有13,000多名有才华和驱动力的专业人士的国际团队塑造了 iGaming 的未来。总部位于吉布拉特，我们的办事处遍及加拿大，印度，曼岛，拉脱维亚，马耳他，罗马尼亚，塞尔维亚，保加利亚和阿联以及更多令人兴奋的目的地。在 ARRISE,我们自豪地创造出各级的增长机会，不断投资于我们的员工，同时欢迎新同事并建立战略伙伴关系，从而开辟新的成功机会。为了实现这一点，我们以自己为代价。我们知道成功是集体努力，我们的团队是由野心，合作和共同致力推动的，而要在每一步都能成长和取得成功。与13,000名 ARRISERS 一起成为 iGaming 未来的一部分！看一个令人兴奋的工作？现在申请，我们的友好的招聘团队将很快联系你。你的旅程在这里开始。你将加入我们的数据科学团队，作为一个在计算机视觉应用研究端工作的数据科学家。你将把开放式问题设置为可测试假设，开发原型来验证它们，并选择适合每个模型架构和方法。计算机视觉是核心领域，可以跨越文本，音频和表格数据进行工作。与 ML 工程师合作，你将帮助验证原型进入生产中并看到它们运行规模化。即使你不满足每种要求，你的技能和产生影响能力最重要。·设计和原型 ML 和深度学习模型，计算机视觉作为主要领域 （对象检测，分类，跟踪）. ·将业务问题设为可测试的假设并开发概念证明来验证它们，以循环根据结果进行评估和基准。· 评价竞争模式架构和预训练模型确定最适合方法。· 与 ML 工程师合作，扩展验证的原型到生产系统中并通过部署保持参与。·追踪实验，管理模型和数据版本化，定义评估指标来比较对象方法。
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ABOUT US
ARRISE sets the benchmark for service delivery and excellence in the iGaming industry. Playing a key role in the success of its clients, which include Pragmatic Play, a brand relied upon by the world’s biggest online casinos for its cutting-edge products, ARRISE helps to deliver exceptional gaming experiences to millions of players worldwide.
Our global team of over 13,000 talented and driven professionals are shaping the future of iGaming. Headquartered in Gibraltar, we have offices spanning Canada, India, the Isle of Man, Latvia, Malta, Romania, Serbia, Bulgaria, and the UAE, and more exciting destinations on the horizon.
At ARRISE, we take pride in creating growth opportunities at all levels, constantly investing in our people while welcoming new colleagues and forging strategic partnerships that open new opportunities for success.
To achieve this, we bet on ourselves. We know that success is a collective effort, and our team is driven by ambition, collaboration, and a shared commitment to grow and succeed — while embracing every step of the journey.
Be part of the future of iGaming with 13,000 ARRISERS! See a job that excites you? Apply now, and our friendly recruitment team will connect with you soon. Your journey starts here.
ABOUT THE ROLE
You will join our Data Science team as a Data Scientist working at the applied-research end of computer vision. You will frame open-ended problems as testable hypotheses, develop prototypes to validate them, and choose the model architectures and methods best suited to each. Computer vision is the core domain, with scope to work across text, audio, and tabular data. Working with ML Engineers, you will help take validated prototypes into production and see them run at scale.
Even if you don't meet every requirement, your skills and ability to deliver impact are what matter most.
WHAT YOU'LL BE DOING
- Design and prototype ML and deep learning models, with computer vision as the primary domain (object detection, classification, tracking).
- Frame business problems as testable hypotheses and develop proofs-of-concept to validate them, iterating on the results.
- Evaluate and benchmark competing model architectures and pre-trained models to identify the best-fit approach.
- Collaborate with ML Engineers to scale validated prototypes into production systems and stay engaged through deployment.
- Track experiments, manage model and data versioning, and define evaluation metrics to compare approaches objectively.
- Work with product, engineering, and business teams to turn objectives into applied ML solutions.
WHAT WE ASK OF YOU
- Master's degree in a relevant field such as Electrical Engineering, Computer Science, or a related quantitative discipline.
- Hands-on experience developing ML and deep learning models, including demonstrated computer vision work.
- Strong proficiency in Python and a deep learning framework (PyTorch or TensorFlow).
- Experience with computer vision models for object detection, image classification, and tracking.
- Solid grounding in deep learning, traditional computer vision, and classical ML.
- Strong experimentation mindset: benchmarking, ablation studies, and structured evaluation of competing approaches.
- Experience working with large, complex datasets.
Nice to have
- Experience collaborating with ML Engineers to bring models into production.
- Experience with any major cloud platform (Azure, AWS, or GCP) for ML training and deployment.
- Familiarity with Docker and CI/CD pipelines.
- Experience with Hugging Face Transformers, vision transformers, or self-supervised / representation learning.
- Exposure to generative AI: prompt engineering, RAG, LLM frameworks (LangChain, LlamaIndex, Haystack), or LLM fine-tuning.
- Background in gaming, iGaming, e-commerce, or other consumer-facing applications at scale.
How we work
Our stack includes Python with PyTorch and TensorFlow, experiment tracking and model versioning, containerized deployment with Docker, and CI/CD pipelines. Data Scientists and ML Engineers work together across the full lifecycle, from early research through to models running in production.
WHAT WE OFFER IN EXCHANGE
- Work on substantial, real-world computer vision and deep learning problems at scale.
- End-to-end involvement, from research and prototyping through to production.
- Opportunities for professional and personal development.
- A collaborative, cross-functional environment with visible impact.
Originally posted on Himalayas