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ML Engineer, AI Models
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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.
About Tenstorrent
Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.
This role sits at the intersection of technical expertise and customer engagement, focused on helping customers and internal teams bring up and optimize AI models on Tenstorrent platforms.
This role is hybrid, based out of Tokyo, Japan.
We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.
Tenstorrentについて
Tenstorrentは、最先端のAI技術で業界をリードし、性能、使いやすさ、コスト効率の常識を変えています。AIによってコンピューティングのあり方が再定義される中、ソフトウェアモデル、コンパイラ、プラットフォーム、ネットワーキング、半導体における技術革新を一体として進化させることが求められています。Tenstorrentの多様な技術者チームは、高性能なRISC-V CPUをゼロから開発してきました。そして、AIへの情熱と、最高のAIプラットフォームをつくりたいという強い思いを共有しています。私たちは、コラボレーション、好奇心、そして難しい課題に真摯に向き合う姿勢を大切にしています。現在、さまざまなレベルの方を歓迎しながらチームを拡大しています。
このポジションは、技術的な専門性と顧客・社内連携の両方が求められる役割であり、顧客や社内チームがTenstorrentプラットフォーム上でAIモデルを立ち上げ・最適化できるよう支援することにフォーカスしています。
本ポジションは日本・東京を拠点としたハイブリッド勤務です。
本ポジションでは、さまざまな経験レベルの候補者を歓迎しています。面接プロセスを通じて適切なレベルを判断し、オファー内容はそのレベルに応じて決定されるため、本求人票上のレベル表記と異なる場合があります.
About the Role
As a Software Engineer on the AI Models / System Bring-Up team, you will help bring up, validate, and optimize AI models on Tenstorrent platforms. You will work across models, runtime software, and hardware to turn research workloads into reliable, high-performance systems.
募集ポジションについて
AI Models / System Bring-UpチームのSoftware Engineerとして、Tenstorrentプラットフォーム上でAIモデルの立ち上げ、検証、最適化を担当していただきます。モデル、ランタイムソフトウェア、ハードウェアを横断して、研究段階のワークロードを安定した高性能システムへとつなげていくポジションです。
Who You Are
-
Experience with deep learning models in at least one major framework such as PyTorch, TensorFlow, or JAX.
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Strong Python or C++ skills and good understanding of neural network architectures, training, and inference workflows.
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Comfortable working in Linux and able to debug issues across software, runtime, and hardware.
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Collaborative and curious, with a degree in Computer Science, Engineering, Applied Mathematics, or a related field, or equivalent practical experience.
- Fluent in English; Japanese proficiency is preferred.
求める人物像
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PyTorch、TensorFlow、JAXなど、主要な深層学習フレームワークのいずれかでのモデル実務経験をお持ちの方
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PythonやC++に強みがあり、ニューラルネットワークの構造、学習、推論の基本理解がある方
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Linux環境での開発に慣れており、ソフトウェア・ランタイム・ハードウェアをまたぐ課題のデバッグができる方
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協調性と好奇心があり、Computer Science、Engineering、Applied Mathematics関連の学位、または同等の実務経験をお持ちの方
- ビジネスレベル日本語と業務遂行が可能な英語力がある方
What We Need
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Bring up and validate AI models such as LLMs, CNNs, recommendation models, and vision models on Tenstorrent hardware and simulators.
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Port models into Tenstorrent toolchains and runtime environments.
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Run experiments to evaluate model accuracy, performance, and stability.
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Debug cross-stack issues and work closely with hardware, compiler, and runtime teams.
お任せする業務
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LLM、CNN、推薦モデル、ビジョンモデルなどのAIモデルをTenstorrentのハードウェアおよびシミュレータ上で立ち上げ、検証すること
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モデルをTenstorrentのツールチェーンおよびランタイム環境へ移植・統合すること
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モデルの精度、性能、安定性を評価するための実験を設計・実施すること
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スタック横断の課題をデバッグし、ハードウェア、コンパイラ、ランタイムの各チームと密に連携すること
What You Will Learn
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How AI models are mapped and optimized on custom AI accelerators.
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How hardware, compiler, runtime, and model teams work together to build production-ready systems.
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Best practices for model bring-up, automation, regression testing, and performance tuning.
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How to translate real-world model requirements into practical technical solutions.
このポジションで得られること
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カスタムAIアクセラレータ上でAIモデルをどのように動かし、最適化していくか
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ハードウェア、コンパイラ、ランタイム、モデルの各チームがどのように連携して実運用向けシステムを作るか
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モデルbring-up、自動化、回帰テスト、性能チューニングのベストプラクティス
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実際のモデル要件を、実用的な技術ソリューションへ落とし込む方法
Nice to Have
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Experience with LLM or foundation model inference, including KV-cache optimization and quantization.
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Background in compiler or runtime engineering for ML workloads.
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Exposure to post-silicon validation, board bring-up, firmware development, or accelerator platforms.
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Experience working directly with customers or field teams on AI workload deployment and debugging.
歓迎要件
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LLMまたは基盤モデル推論の経験（KV-cache最適化、量子化を含む）
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MLワークロード向けのコンパイラまたはランタイム開発の経験
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ポストシリコン検証、ボードbring-up、ファームウェア開発、アクセラレータ基盤に関する経験
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AIワークロードの導入やデバッグで、顧客やフィールドチームと直接連携した経験
This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology. Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2). These requirements apply to persons located in the U.S. and all countries outside the U.S. As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency. If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.
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Senior Machine Learning Scientist (Ad Cloud, RTB) - Tokyo,Japan
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About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
Open to overseas candidates/Visa Support
This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you’ll further improve bidding strategies, audience targeting and creative optimization by deep-diving RTB ecosystem including SSP/DSP/MMP to design the strategy, enhancing user signals or applying advanced deep learning model
What You’ll Work On
- Deep-dive the RTB ecosystem to identify the potential direction and decide the bidding strategy
- Leverage advance deep learning model to improve bidding/audience model performance
- Co-work with teams to improve real-time/long-term user interaction signal collection and to further improve model performance
What We’re Looking For
- Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
- 3+ years of industry experience on RTB ecosystem
- Proficiency in Python and SQL experience with modern ML frameworks and deep learning model (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills.
#LI-AK1
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新型ロボットに関する研究・開発(知能化領域)
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| 職務内容 | ======================== リモート面接を実施中です ======================== 【募集背景】 Hondaはこれまで、人の可能性を拡げ、人生を自由で豊かにするため、ASIMOをはじめとするロボティクス研究に継続的に取り組んできました。 次世代に向けては、時間や空間の制約に縛られず、バーチャルに自己能力を拡張するHondaアバターロボットや、UNI-CUBにように重心を変えるだけで無意識に移動ができる搭乗型ロボットの研究開発を進めております。 人々の役に立ちワクワクするロボティクス社会の未来を実現するために、ロボットの自律制御技術，遠隔操縦技術、軽量・安全の要素技術、極限環境での耐環境性技術などの開発を、共に悩み、共に考え、共に実践して頂ける、チャレンジングなモチベーションを持った仲間を募集しています。 従来の価値観にとらわれず、ロボット・モビリティの新しい可能性を探究し続け社会に役立つ次世代のロボット・モビリティを一緒に創ってみませんか。 【具体的には】 ※ご経験/スキルに合わせて詳細業務を決定します。ロボット（ロボットアーム・ハンド等）を用いた自律マニピュレーション、遠隔操縦における ①機械学習 ・さまざまな人のスキルを模倣学習するアルゴリズムの研究開発 ・データを用いた推定及び制御の学習アルゴリズムの研究開発 ②動作生成 ・ロボットの状況推定にもとづく動作制御アルゴリズムの研究開発 ・状況予測にもとづく最適動作生成アルゴリズムの研究開発 ③人・環境認識 ・人の動作予測や環境理解のための画像認識やセンシング技術の研究開発 ・人の意図推定技術の研究開発 ※学会への参加の機会もございます。 ※国内外の社内関連部署や海外の研究所との連携もございます。 【製品例】 ・バーチャルな移動を可能にする「Hondaアバターロボット」に関しては【こちら】 ・ASIMOについては【こちら】 ・UNI-CUBについては【こちら】 ・高所調査用ロボットについては【こちら】 【使用ツール】 ・TensorFlow/PyTorchなどの深層学習フレームワーク ・SciPy/scikit-learnなどの科学技術計算、機械学習パッケージ ・ROSをはじめとするロボティクスにおけるソフトウェア開発にて使用されるOSSライブラリや開発環境 ・Bullet/MuJoCoなどの物理演算エンジン ・C/C++/Python ・Gitなどのバージョン管理システム 【魅力・やりがい】 「人と協調する人工知能技術」、Cooperative Intelligenceの研究、プロダクトの開発、フィジビリティスタディまでを一連で手掛ける業務であり「人」を軸とした研究アプローチをとることで新しい価値を創造し、社会に貢献することができます。 自主性が尊重され、課題に対して自らの意思のある挑戦が許されるため、新しい技術に挑戦し、世の中に新しい価値を提案したいという思いを実現できるやりがいのある環境です。 【職場環境・風土】 「買う喜び、売る喜び、創る喜びを世界に広げる」を基本理念に、Hondaでは数々の独創的な製品を創業から生みだし続けてきました。 Hondaには役員から現場社員まで、あらゆる人材が自由な発想で、夢や理想を徹底的に追求する風土が根付いており、学歴や年齢に関係なく誰もがフラットに活躍できる職場環境です。 ※Hondaの中途採用募集職種一覧は【こちら】 |
| 応募資格 | 【求める経験・スキル】下記いずれかの経験をお持ちの方 ・大学などでのAI関連技術の研究経験 ・ソフトウェア開発のご経験(プログラミング) 【上記に加え、あれば望ましい経験、スキル】 ・ロボット工学および、制御工学に関する知識 ・ROS(Robot Operating System)に関する知識 ・最適化に関する知識 【求める人物像】 ●夢を持ち、高い目標を掲げてやりきるエネルギーのある方 ●Hondaの目指すロボティクス社会のビジョンに共感して頂ける方 ●目的に対して部署横断的に活動できる行動力を持った方 ●技術に対して論理的に説明できて周囲を巻き込んで問題を解決できる方 ●変化を許容し柔軟に対して能動的に取り組める方 ●自己の意思や想いを発信しながら他人やチームを尊重しプロジェクトに貢献できる方 ●お客様先、海外拠点などを含めて、未開の地に飛び込んでいける方 ●常に利用者視点でものごとを捉えて、具体的な解決策を試行できる方 ●責任を持って最後までやりきる力を持った方 ●10年後に一緒に働いていて良かったと思える方 |
| 待遇 | 待遇・福利厚生（受動喫煙防止措置含む） ■勤務/休日/休暇 ・勤務は応募職種毎に設定（フレックスタイム制・固定制・交替制） ・リモートワーク制度 ・長期休暇あり（GW、夏季、年末年始） ・年間休日121日 ・平均有休取得日数19.5日（2021年度） ・年次有給休暇…16日～20日/年 ※勤続年数に応じて付与 ・慶弔休暇（結婚休暇…6日、忌引休暇…1～7日※続柄に応じて付与） ■各種手当 ・通勤手当 ・リモートワーク手当 ・賞与 ・残業代全額支給 ■福利厚生 ・独身寮、転勤社宅 ※適用条件有 ・社内研修（階層別研修、ビジネススキル研修、語学研修等） ・語学資格取得支援 ・健康診断 ・余暇施設（運動施設、保養所） ・厚生制度（財形貯蓄制度、団体扱い保険、持家支援、持株会制度、選択型福利厚生等） ・食堂施設、食事補助 ■両立支援（仕事と育児・介護など） ・育児・介護手当 ・リモートワーク制度 ・短時間勤務制度 ・育児・介護休職 ・産前産後休暇 ・産後パートナー休暇（出生8週以内に5日） ・子の看護休暇（年間5日/子供1人当たり） ・育児費用補助 ・社内託児所（和光/栃木） ・介護休暇（年間5日/要介護者1人当たり） ・不妊治療休暇（年間5日） ・不妊治療休職（原則6か月、最大1年） ・病気治療休暇（会社指定の疾患を対象・年間5日） |
| 勤務地 | ●本田技術研究所 先進技術研究所 （埼玉県和光市） |
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Staff/Senior Machine Learning Scientist (Ad Cloud) - Tokyo,Japan
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About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
Open to overseas candidates/Visa Support
This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.
What You’ll Work On
- Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
- Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
- Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
- Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).
What We’re Looking For
- Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
- 4+ years of industry experience in ad tech, with a focus on performance optimization.
- Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
- Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
- Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).
#LI-AK1
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Senior Machine Learning Scientist, Playable Ads
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About Appier
Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.
About the role
AI is reshaping how brands connect with consumers — and at Appier, we’re at the forefront. Our Playable Ads team builds AI-powered ad experiences — from interactive playable formats to video ads — that drive dramatically higher engagement and conversion for the world’s leading apps and games. We’re looking for a Senior Machine Learning Scientist to push the boundaries of what’s possible — applying cutting-edge ML, generative AI, and optimization techniques to create smarter, more compelling ad creatives at scale.
If you’re excited about turning the latest advances in AI into products that reach millions of users, and you thrive at the intersection of research and real-world impact, we’d love to talk.
What You’ll Work On
- Apply ML and generative AI techniques to problems such as creative optimization, user behavior prediction, engagement modeling, and dynamic content generation for various creative formats.
- Own the end-to-end ML lifecycle — from problem framing and experimentation through to production deployment and continuous improvement.
- Collaborate closely with product, engineering, and design teams to translate business goals into well-defined ML solutions.
- Conduct offline and online evaluation, A/B testing, and performance monitoring to continuously improve model quality and business impact.
- Stay current with the latest research in areas like LLMs, multimodal models, reinforcement learning, and recommendation systems, and proactively propose innovative applications to the team.
- Mentor fellow scientists and contribute to the team’s technical standards and culture.
What We’re Looking For
[Minimum qualifications]
- Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a related field.
- Solid understanding of modern ML models and algorithms, with hands-on experience in at least one area such as prediction/optimization, generative models, recommendation systems, computer vision, or reinforcement learning.
- Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
- Practical experience taking ML models from prototype to production, including pipeline development and performance monitoring.
- Strong analytical and problem-solving skills with the ability to diagnose model behavior and improve training pipelines.
- Clear communicator who can explain technical ideas to both technical and non-technical stakeholders and enjoys working in a fast-paced, collaborative environment.
- Proficient in using LLM-powered development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to accelerate productivity.
- Ability to balance cutting-edge research with time-to-market constraints, delivering iterative PoCs that validate product hypotheses and translate into production-ready solutions.
[Preferred qualifications]
- Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, KDD, RecSys).
- Experience in the advertising technology or MarTech domain.
- Contributions to open-source projects or active involvement in research communities.
#LI-AK1
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About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
Open to overseas candidates/Visa Support
This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
Our engineering team has a solid technical background, which would be a great environment for a skilled engineer.
In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.
What You’ll Work On
- Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
- Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
- Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
- Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).
What We’re Looking For
- Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
- 5+ years of industry experience in ad tech, with a focus on performance optimization.
- Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
- Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
- Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).
Language
Fluent in English or Chinese.
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About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.
What You’ll Work On
- Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
- Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
- Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
- Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).
What We’re Looking For
- Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
- 4+ years of industry experience in ad tech, with a focus on performance optimization.
- Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
- Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
- Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).
#LI-AK1
Ready to apply?
Apply to Appier
About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you’ll build identify graph to enrich unified customer profile and also identify high purchase value users to drive ROAS by machine learning model.
What You’ll Work On
- Leverage scientific methods to build identify graph and identify high-value users
- Drive online experiments to continuously improve ROAS
- Own the project independently.
- Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.
What We’re Looking For
- Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
- 3+ years of industry experience on identify graph, ID mapping and cross-device mapping in digital Ads related fields, and generate mapping and profile under large-scale data.
- Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills.
#LI-AK1
Ready to apply?
Apply to Appier
Senior Machine Learning Scientist (Ads incrementality) - Tokyo
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About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.
Open to overseas candidates/Visa Support
This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you'll measure ads incrementality on different type of traffic, creative, users, and also improve campaign efficiency on combination having good incrementality by machine learning model and AI automation.
What You’ll Work On
- Leverage scientific methods to improve ads measurement.
- Drive online experiments to continuously improve ads effectiveness.
- Own the project independently.
- Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.
What We’re Looking For
- Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, Econometrics, or related field.
- 3+ years of industry experience on causal inference, incrementality, marketing mix modeling or other measurement solutions on digital Ads related fields, and understand the assumption and difference across methods.
- Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills.
Language
Fluent in English or Chinese.
#LI-AK1
Ready to apply?
Apply to Appier
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