Join Proton and build a better internet where privacy is the default

Proton was founded in 2014 by scientists from CERN on a simple truth: privacy is a fundamental human right. Since then, we’ve built the world’s largest encrypted email service (Proton Mail) and expanded into Proton VPN, Proton Drive, Proton Pass, and Proton Calendar—tools used by millions globally to protect their freedom, fight censorship, and keep their data safe. In some situations, Proton has literally helped save lives!

We are profitable, independent (no VC control), and selectively hire from the top ~1% of applicants. Our 500+ team members across 50+ countries come from leading organizations and elite academic backgrounds. We move fast, keep hierarchy light, and prioritize impact over optics. If you want to do meaningful work with exceptionally high-caliber people, this is it. Join us and do work you can truly be proud of. Check our open-source projects here!

Purpose of the role:

We are looking for a MLOps / Infrastructure Engineer to join the MSA (Mail Security & Anti-abuse) team and support the operation and evolution of our machine learning anti-abuse systems.
MSA is a multidisciplinary group created in 2019 to tackle complex problems in mail delivery, spam prevention, abuse detection, and account security across the Proton ecosystem. Our systems combine human expertise and machine learning to make tens of millions of decisions daily, protecting users from spam, fraud, account compromise, and large-scale attacks.
Today, our focus areas include:

• Mail delivery and spam protection
• Abuse detection and account security
• Site reliability across Proton services
• New products such as Wallet and Lumo

Our systems have reduced spam misclassifications by over 60%, blocked millions of abusive signups, protected hundreds of thousands of users from account compromise, and mitigated hundreds of large-scale attacks.
To move fast with limited resources, we operate as autonomous teams owning systems end-to-end across infrastructure, backend, data, ML, and operations. In just a few years, we have grown from 2 to over 60 engineers and analysts across three continents, providing 24/7 protection to millions of users.
We are looking for humble, mission-driven engineers who enjoy learning, improving systems, and making a real-world impact.
This role is ideal for someone early in their career who wants to build strong foundations in infrastructure, automation, and production ML systems. You will work closely with experienced engineers to deploy, monitor, and maintain critical services that run 24/7 and protect millions of Proton users.

What you will do:

As an MLOps / Infrastructure Engineer, you will contribute to the reliable operation and continuous improvement of systems protecting millions of Proton users.

• Assist in maintaining the operational stability of machine learning and anti-abuse systems running 24/7
• Support deployment and maintenance of services and infrastructure under guidance from senior engineers
• Help implement and improve logging, monitoring, and alerting for production systems
• Participate in debugging and resolving production incidents with team support
• Contribute to CI/CD pipelines and deployment automation workflows
• Assist in deploying and maintaining containerized services using Docker and related tools
• Support infrastructure automation efforts through scripting and configuration management
• Document operational procedures and deployment processes
• Gradually take ownership of infrastructure components and improvements as experience grows

Job requirements:

• Experience with Linux system fundamentals (command line, systemd, troubleshooting)
• Proficiency in scripting languages (Bash and Python)
• Familiarity with Docker and containerization concepts
• Basic understanding of CI/CD pipelines and automated deployments
• Basic familiarity with databases such as MySQL or similar systems
• Experience with Git and collaborative development workflows
• Strong problem-solving mindset and ability to work and learn in a fast-paced global team
• Willingness to participate in on-call rotations after initial ramp-up
• Strong communication skills in English (written and verbal)

• Hands-on experience with Ansible, Puppet, or similar configuration management tools
• Familiarity with data processing and workflow orchestration tools (Airflow, Dask)
• Experience deploying services to production environments (personal projects count)
• Exposure to monitoring and observability tools (Prometheus, Grafana, ELK)
• Basic understanding of machine learning workflows or data pipelines
• Familiarity with Terraform, Kubernetes, or cloud infrastructure platforms

Even if you don’t meet all the requirements listed above, but feel you could still be a great fit, please still apply.

What We Offer

• Work that Matters: millions of people trust Proton with their privacy. We answer only to our users — not advertisers, not investors with conflicting agendas, not governments. The work you do here is real, and the impact is measurable. (read more about our impact here)
• A great Team: Our team is diverse, collaborative, and tight-knit with people coming from all walks of life, including many of the world’s top academic institutions and organizations, such as MIT, Harvard, Stanford, Caltech, Cambridge, and ETH.
• Technology: you'll get the right hardware and the right software you need to do your best work.
• Learning & Development: we invest in your growth because sharp people make us better. Proton is one of the fastest ways to accelerate your career because you'll be thrown into real challenges, with real ownership, from day one.
• Employee Benefits: your wellbeing isn't an afterthought. We offer strong health coverage, solid retirement options, generous leave, and wellness support so you can bring your best self to work every day
• Stock Options: at Proton, we all have the opportunity to be owners of the company. From day one, you have a real stake in what we're building. When Proton wins, you win.
• In-Person Collaboration: Amazing things happen when passionate, smart, and purposeful people get together in the same room. With offices across Geneva, Zürich, Barcelona, London and more, you'll spend most of your time collaborating face-to-face with people who genuinely care about what they're building
• Food: Lunch and snacks are on us every day in our offices so you can focus on the work and not on what's for lunch.
• Transport: getting to the office shouldn't cost you. We cover public transport, bike allowances, or parking, whichever works for you.
• Flexible Working: you own your schedule. Set hours that work for you and your team — because outcomes matter more than when the clock says you started.
•  

Our Commitment to Diversity and Inclusion

At Proton, we believe diversity drives innovation and strengthens our mission to provide privacy as a default for all. We are committed to fostering an inclusive environment where all individuals, regardless of race, ethnicity, gender, age, sexual orientation, physical ability, or socio-economic background, feel valued and empowered. We strive to create equal opportunities, promote open dialogue, and support continuous learning to ensure every voice is heard and respected.

If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know.

Candidate Privacy Notice

When you apply for a position, refer a candidate, or are considered for a role at Proton Technologies AG (Proton, we, us, or our), your information is stored in Greenhouse, in accordance with their Service Privacy Policy. This information is used to evaluate your suitability for the posted position. We also retain this information for consideration for future roles that you may apply for or that we believe may align with your background and skills.

If we no longer have a legitimate business need to process your information, we will either delete or anonymize it. Should you have any inquiries about how we use or manage your information, or if you wish to access, correct, or delete your data, please contact our privacy team at careers@proton.ch.

Proton does not accept unsolicited resumes from any sources other than directly from candidates. We will not pay a fee for any placement resulting from an unsolicited offer, even if the candidate is subsequently hired by Proton.

To learn more about our privacy policy, please visit our privacy policy page.

#LI-ONSITE

Join Proton and build a better internet where privacy is the default

Proton was founded in 2014 by scientists from CERN on a simple truth: privacy is a fundamental human right. Since then, we’ve built the world’s largest encrypted email service (Proton Mail) and expanded into Proton VPN, Proton Drive, Proton Pass, and Proton Calendar—tools used by millions globally to protect their freedom, fight censorship, and keep their data safe. In some situations, Proton has literally helped save lives!

We are profitable, independent (no VC control), and selectively hire from the top ~1% of applicants. Our 500+ team members across 50+ countries come from leading organizations and elite academic backgrounds. We move fast, keep hierarchy light, and prioritize impact over optics. If you want to do meaningful work with exceptionally high-caliber people, this is it. Join us and do work you can truly be proud of. Check our open-source projects here!

About the role:

The MSA team (Mail Delivery, Spam, and Anti-Abuse) is a multidisciplinary group founded in 2019 to solve complex security challenges across the Proton ecosystem. We build sophisticated systems from scratch that combine human intelligence and machine learning to make tens of millions of real-time or asynchronous decisions daily. Our focus areas include:

1. Mail delivery and spam prevention

2. Abuse detection

3. Account security

4. Site reliability and resilience

Over the past few years, our custom systems have:

• Reduced spam filter misclassifications by over 70%

• Blocked millions of abusive bulk signups

• Protected hundreds of thousands of users from account compromises

• Mitigated hundreds of DDoS attacks

Recently, we’ve expanded our impact with Proton Sentinel (an AI-human hybrid security program) and Proton CAPTCHA (our own puzzle system to detect and prevent abuse). We’re now scaling our capabilities with agentic AI to enable autonomous threat detection and response.

In 5 years, we’ve grown from 2 engineers to 40+ engineers and analysts across 3 continents, operating 24/7. We’re looking for curious, collaborative, and impact-driven engineers who thrive in a startup environment and want to shape the future of secure AI.

What You Will Do

• Design and deploy scalable ML systems using modern MLOps practices, including real-time inference, model monitoring, and automated retraining pipelines.

• Architect agentic AI systems capable of autonomous threat detection, adaptive policy enforcement, and self-healing security responses.

• Build tools for model development, debugging, and explainability to accelerate iteration and transparency.

• Optimize ML workflows for distributed environments to handle large-scale data processing.

• Collaborate cross-functionally with security analysts, backend/frontend engineers, and customer support to align technical solutions with user needs.

• Advance the state of ML for anti abuse and account security, exploring cutting-edge techniques like adversarial robustness, graph-based anomaly detection, and privacy-preserving AI.

What You Bring

• Degree in Computer Science or a related quantitative field, with 2+ years hands-on experience in building and running ML systems.

• Production-level ML expertise: You’ve shipped models that handle real-world scale and complexity.

• Hands-on experience with LLMs in agentic environments.

• Strong software engineering skills: Proficiency in Python, with a solid understanding of backend and server fundamentals.

• Statistical rigor: Deep understanding of probability, hypothesis testing, and experimental design.

• Experience with adversarial ML or red-teaming ML systems.

• Experience working on distributed systems.

• Contributions to open-source security/privacy tools.

• Knowledge of federated learning, differential privacy, or on-device inference.

• Familiarity with graph-based anomaly detection or knowledge graphs.

• Technical leadership: Experience owning projects, mentoring peers, and driving technical direction.

• Security mindset: Familiarity with abuse patterns, adversarial attacks, or threat intelligence (bonus points!).

Why Join Us?

• Impact at scale: Your work will protect millions of users globally.

• Cutting-edge tech: Tackle challenges like agentic AI, real-time threat detection, and privacy-preserving ML.

• Collaborative culture: Work with a global team of experts in security, ML, and systems engineering.

• Growth opportunities: Lead initiatives, mentor other, and learn across a diverse technology stack

• Mission-driven: Contribute to a privacy-first internet where users control their data.

What We Offer

• Work that Matters: millions of people trust Proton with their privacy. We answer only to our users — not advertisers, not investors with conflicting agendas, not governments. The work you do here is real, and the impact is measurable. (read more about our impact here)
• A great Team: Our team is diverse, collaborative, and tight-knit with people coming from all walks of life, including many of the world’s top academic institutions and organizations, such as MIT, Harvard, Stanford, Caltech, Cambridge, and ETH.
• Technology: you'll get the right hardware and the right software you need to do your best work.
• Learning & Development: we invest in your growth because sharp people make us better. Proton is one of the fastest ways to accelerate your career because you'll be thrown into real challenges, with real ownership, from day one.
• Employee Benefits: your wellbeing isn't an afterthought. We offer strong health coverage, solid retirement options, generous leave, and wellness support so you can bring your best self to work every day
• Stock Options: at Proton, we all have the opportunity to be owners of the company. From day one, you have a real stake in what we're building. When Proton wins, you win.
• In-Person Collaboration: Amazing things happen when passionate, smart, and purposeful people get together in the same room. With offices across Geneva, Zürich, Barcelona, London and more, you'll spend most of your time collaborating face-to-face with people who genuinely care about what they're building
• Food: Lunch and snacks are on us every day in our offices so you can focus on the work and not on what's for lunch.
• Transport: getting to the office shouldn't cost you. We cover public transport, bike allowances, or parking, whichever works for you.
• Flexible Working: you own your schedule. Set hours that work for you and your team — because outcomes matter more than when the clock says you started.

Our Commitment to Diversity and Inclusion

At Proton, we believe diversity drives innovation and strengthens our mission to provide privacy as a default for all. We are committed to fostering an inclusive environment where all individuals, regardless of race, ethnicity, gender, age, sexual orientation, physical ability, or socio-economic background, feel valued and empowered. We strive to create equal opportunities, promote open dialogue, and support continuous learning to ensure every voice is heard and respected.

If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know.

Candidate Privacy Notice

When you apply for a position, refer a candidate, or are considered for a role at Proton Technologies AG (Proton, we, us, or our), your information is stored in Greenhouse, in accordance with their Service Privacy Policy. This information is used to evaluate your suitability for the posted position. We also retain this information for consideration for future roles that you may apply for or that we believe may align with your background and skills.

If we no longer have a legitimate business need to process your information, we will either delete or anonymize it. Should you have any inquiries about how we use or manage your information, or if you wish to access, correct, or delete your data, please contact our privacy team at careers@proton.ch.

Proton does not accept unsolicited resumes from any sources other than directly from candidates. We will not pay a fee for any placement resulting from an unsolicited offer, even if the candidate is subsequently hired by Proton.

To learn more about our privacy policy, please visit our privacy policy page.

#LI-ONSITE

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.

About the role

Appier's Playable Ads team (https://www.appier.com/en/blog/what-is-playable-ads)  builds AI-powered playable and video ad experiences that drive dramatically higher engagement and conversion for the world's leading apps and games. We're looking for a Senior Backend Developer with deep expertise in distributed systems and modern backend architecture to design and build the scalable, high-performance services behind these experiences — from creative generation pipelines to the infrastructure that brings our ML models to production. You'll work across microservices, messaging systems, data persistence layers, and system performance optimization, while partnering with ML scientists on MLOps workflows to continuously ship and serve new model versions to end users. You'll also collaborate closely with frontend engineers and product managers to deliver seamless, cross-functional outcomes.

If you're passionate about building backend systems that operate at scale, thrive in cross-functional teams, and want your code to directly power AI-driven ad experiences reaching millions of users, we'd love to talk.

What You'll Work On

• Architect and develop robust, scalable backend services and APIs using ASP.NET Core, owning sizable projects from system design through production operation.
• Design efficient database schemas and optimize data access logic across SQL and NoSQL data stores.
• Implement message-driven communication with high reliability and fault tolerance.
• Partner with ML scientists to build and maintain MLOps pipelines — including model versioning, deployment, serving, and monitoring — ensuring new models are reliably delivered to production.
• Lead system designs, drive technical roadmap decisions, and provide guidance to team members.
• Proactively identify performance bottlenecks, profile critical components, and implement scalable solutions.
• Own and continuously improve system observability, incident management, CI/CD pipelines, and deployment workflows.
• Explore and integrate AI-assisted development tools and emerging technologies to boost team productivity.
• Participate in on-call rotation to ensure product reliability and scalability.

What We're Looking For 

[Minimum qualifications]

• Proficiency in C# and ASP.NET Core, or experience with other object-oriented languages (e.g., Java, Go) with willingness to cross-train in the .NET stack.
• Proven experience in distributed systems, microservice architectures, and designing scalable backend systems.
• Strong expertise in PostgreSQL, MongoDB, or equivalent SQL/NoSQL databases, with hands-on experience in ORM frameworks such as Entity Framework Core.
• Advanced knowledge of message broker systems such as RabbitMQ, Kafka, or NATS.
• In-depth understanding of IO-bound operations, threading, parallelism, and asynchronous programming.
• Practical experience with Docker, container-based deployment workflows, and cloud platforms (AWS, GCP, or Azure).
• Hands-on experience with CI/CD pipelines, observability tooling, and production operational practices.
• Demonstrated ability to write clean, well-documented code and solve complex problems analytically.
• Clear communicator who can explain technical decisions 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.

[Preferred qualifications]

• BS/MS degree in Computer Science or a related field.
• Experience with MLOps practices such as model serving infrastructure, A/B testing frameworks, or ML pipeline orchestration tools.
• Leadership experience such as mentoring junior engineers, leading code reviews, or facilitating agile processes.
• Experience with performance profiling and debugging tools, high-performance network services, or FFI integrations for performance-critical components.
• Solution-oriented mindset with a focus on system sustainability, and willingness to explore emerging technologies into backend systems.

[Language]

Fluent in English, Japanese language proficiency is not required.

Open to overseas candidates/Visa Support
This position can be based in Tokyo, Japan or Taipei, Taiwan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth relocation transition to Japan.

#LI-AK1

About the role 

We are seeking an experienced Machine Learning Lead to helm our Machine Learning team. 

In this pivotal role, you will be the engineering architect behind Vulcan’s core AI capabilities. You will act as the nexus between Research, Platform, and Product. Your mission is to translate cutting-edge findings on GenAI threats into robust, production-ready machine learning models that power our GenAI Security Guardrails (Blue Team) and Automated Vulnerability Assessment (Red Team). 

Crucially, you will serve as the bridge between deep tech and business strategy, articulating technical constraints (like FLOPS and latency) to leadership and clients while guiding the engineering direction. 

Key Responsibilities

1. Model Development & Optimization (Training & Fine-tuning):

• Research to Production: Collaborate with the Security Research Team to operationalize new threat detection techniques. They identify the "what" (e.g., new prompt injection patterns); you determine the "how" (model architecture, training strategy). 
• Fine-tuning & Adaptation: Lead the fine-tuning of Language Models (e.g., using LoRA/PEFT) to optimize for our supported muti-lingual languages and specific security intents.
• Multimodal Readiness: Prepare the system for Multimodal (Text + Image/Audio) capabilities. Evaluate and implement models to detect visual prompt injections and non-textual threats as the product evolves. 

2. MLOps& Data Infrastructure: 

• Enhance & Scale MLOps: Take ownership of our existing ML pipelines. Focus on optimizing and scaling CI/CD/CT workflows to improve training efficiency and deployment velocity. 
• Data Governance: Implement and enforce rigorous Data Versioning strategies (e.g., DVC) to ensure complete reproducibility of model artifacts and datasets.
• Monitoring & Reliability: Maintain rigorous monitoring for model drift and performance, ensuring high reliability in a production security environment.

3. Cross-Functional Implementation & Leadership:

• Platform Collaboration: Work closely with the Platform Engineering Team to integrate ML models into the broader product architecture. Ensure seamless interaction between model inference services and the main platform logic. 
• Team Leadership: Lead and mentor Machine Learning Engineers, fostering a culture of engineering rigor, code quality, and operational excellence.
• Resource Management: Manage GPU resources and compute budgets effectively for both training and inference workloads. 

4. Technical Strategy & Stakeholder Management:

• Translating Tech to Business: Act as the technical voice of the ML team. You must effectively explain complex ML concepts (e.g., FLOPS, quantization trade-offs, model latency vs. accuracy) to executive leadership and clients. 
• Cost-Benefit Analysis: Justify compute resource investments. Articulate the trade-off between infrastructure costs (GPU hours) and performance gains to non-technical stakeholders. 

Qualifications

• Experience: 5+ years in Machine Learning Engineering, with specific experience in leading technical projects or mentoring engineers.
• Communication & Business Acumen: Exceptional ability to distill complex technical topics (e.g., compute complexity, infrastructure costs) into clear, business-relevant insights for decision-makers.
• MLOps Proficiency: Proven experience in optimizing ML pipelines and infrastructure. Familiarity with tools like MLflow, Kubeflow, Airflow, and Data Versioning tools (DVC, etc.).
• Engineering First: Proficient in Python, Docker, and Kubernetes. You treat ML models as software artifacts that need testing and version control.
• NLP & LLM Expertise: Experience with Transformer architectures, Embeddings, and LLM fine-tuning. Familiarity with frameworks like PyTorch, Hugging Face, and vLLM.
• Language Support: Experience processing or fine-tuning models for multi-lingual environments. 

Nice to Have

• Multimodal Expertise: Experience working with Multimodal models (Image-to-Text, Text-to-Image, VLMs like CLIP, LLaVA).
• Security Awareness: Understanding of GenAI security threats (e.g., Prompt Injection).
• High-Performance Computing: Experience optimizing inference speed (quantization, distillation, vLLM) for real-time applications.
• Vector Database: Experience with Vector DBs for RAG applications. 

Why Join Us? 

• Innovative Environment: Be part of a company at the forefront of technology to provide security in GenAI, with opportunities to work on groundbreaking projects. 
• Growth Opportunities: Take your career to new heights with our career development programs and growth-focused culture. 
• Dynamic Team: Join a multi-cultural and dynamic team of dedicated professionals who inspire and support each other. 
• Compensation: Competitive salary and benefits package, commensurate with experience and performance. 

Application Process 

• If you're ready to embark on this exciting journey and contribute to shaping the future of GenAI security, please submit your resume outlining your relevant experience and motivation for applying.
• If you prefer a direct connection or have specific questions about our vision, feel free to reach out to our Co-founder, Alvin Kwock, via LinkedIn. 

About the role 

We are seeking an experienced Machine Learning Lead to helm our Machine Learning team. 

In this pivotal role, you will be the engineering architect behind Vulcan’s core AI capabilities. You will act as the nexus between Research, Platform, and Product. Your mission is to translate cutting-edge findings on GenAI threats into robust, production-ready machine learning models that power our GenAI Security Guardrails (Blue Team) and Automated Vulnerability Assessment (Red Team). 

Crucially, you will serve as the bridge between deep tech and business strategy, articulating technical constraints (like FLOPS and latency) to leadership and clients while guiding the engineering direction. 

Key Responsibilities

1. Model Development & Optimization (Training & Fine-tuning):

• Research to Production: Collaborate with the Security Research Team to operationalize new threat detection techniques. They identify the "what" (e.g., new prompt injection patterns); you determine the "how" (model architecture, training strategy). 
• Fine-tuning & Adaptation: Lead the fine-tuning of Language Models (e.g., using LoRA/PEFT) to optimize for our supported muti-lingual languages and specific security intents.
• Multimodal Readiness: Prepare the system for Multimodal (Text + Image/Audio) capabilities. Evaluate and implement models to detect visual prompt injections and non-textual threats as the product evolves. 

2. MLOps& Data Infrastructure: 

• Enhance & Scale MLOps: Take ownership of our existing ML pipelines. Focus on optimizing and scaling CI/CD/CT workflows to improve training efficiency and deployment velocity. 
• Data Governance: Implement and enforce rigorous Data Versioning strategies (e.g., DVC) to ensure complete reproducibility of model artifacts and datasets.
• Monitoring & Reliability: Maintain rigorous monitoring for model drift and performance, ensuring high reliability in a production security environment.

3. Cross-Functional Implementation & Leadership:

• Platform Collaboration: Work closely with the Platform Engineering Team to integrate ML models into the broader product architecture. Ensure seamless interaction between model inference services and the main platform logic. 
• Team Leadership: Lead and mentor Machine Learning Engineers, fostering a culture of engineering rigor, code quality, and operational excellence.
• Resource Management: Manage GPU resources and compute budgets effectively for both training and inference workloads. 

4. Technical Strategy & Stakeholder Management:

• Translating Tech to Business: Act as the technical voice of the ML team. You must effectively explain complex ML concepts (e.g., FLOPS, quantization trade-offs, model latency vs. accuracy) to executive leadership and clients. 
• Cost-Benefit Analysis: Justify compute resource investments. Articulate the trade-off between infrastructure costs (GPU hours) and performance gains to non-technical stakeholders. 

Qualifications

• Experience: 5+ years in Machine Learning Engineering, with specific experience in leading technical projects or mentoring engineers. 

• Communication & Business Acumen: Exceptional ability to distill complex technical topics (e.g., compute complexity, infrastructure costs) into clear, business-relevant insights for decision-makers. 

• MLOps Proficiency: Proven experience in optimizing ML pipelines and infrastructure. Familiarity with tools like MLflow, Kubeflow, Airflow, and Data Versioning tools (DVC, etc.). 

• Engineering First: Proficient in Python, Docker, and Kubernetes. You treat ML models as software artifacts that need testing and version control. 

• NLP & LLM Expertise: Experience with Transformer architectures, Embeddings, and LLM fine-tuning. Familiarity with frameworks like PyTorch, Hugging Face, and vLLM. 

• Language Support: Experience processing or fine-tuning models for multi-lingual environments. 

Nice to Have

• Multimodal Expertise: Experience working with Multimodal models (Image-to-Text, Text-to-Image, VLMs like CLIP, LLaVA). 

• Security Awareness: Understanding of GenAI security threats (e.g., Prompt Injection). 

• High-Performance Computing: Experience optimizing inference speed (quantization, distillation, vLLM) for real-time applications. 

• Vector Database: Experience with Vector DBs for RAG applications. 

Other Benefits 

To us, people are our greatest asset, and we are more than happy to invest in employees! We create a healthy work atmosphere and provide you with the tools and support for doing your job successfully. With a culture of flexibility and transparency, we believe there should be no barriers, and everyone’s contributions matter. 

Work Life Balance is a must  

• 15 days annual leaves (pro-rata for partial month at first year) 
• 5 days full-pay sick leaves, 3 days menstrual leaves 
• Health check subsidy 
• Ergonomic-design chair and fully-equipped devices for work
• Hybrid remote work and flexible working hour.

Grow together & keep learning

• Conferences & external subsidy 
• Learning clubs to share technical skill (e.g: Frontend/Backend tech sharing, Blockchain...etc) 

Work Hard, Play even Harder 

• Various entertainment & sports clubs, attend basketball clubs today, and play board game tomorrow! 
• Snacks & beverage to refill your energy anytime 

About Appier

Appier is a software-as-a-service (SaaS) 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.

About the Role

We are looking for a Senior Software Engineer, Machine Learning to join the Enterprise Solution Science Team. 
This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.
In this role, you will help bridge the gap between research and production by building and optimizing scalable, high-performance ML infrastructure — including data pipelines, dashboards, and monitoring systems.

What You’ll Work On

• Design and operate robust ML job execution frameworks for training, inference, and post-processing.
• Build and maintain internal API servers and developer tools to orchestrate ML jobs on Kubernetes (via Argo Workflows, Helm, Terraform).
• Architect, implement, and scale batch (Spark) pipelines for ML training and evaluation.
• Design and monitor data infrastructure using PostgreSQL and other databases.
• Ensure high availability and observability through monitoring tools like Prometheus and Grafana.
• Create internal tools and services to simplify ML experimentation and production workflows.
• Collaborate closely with ML scientists to turn research outputs into user-facing product features
• Partner with engineers, PMs, and other cross-functional teams to deliver high-quality AI products

What We’re Looking For (Minimum)

• Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s degree preferred)
• 3+ years of practical experience in ML platform engineering, MLOps, or data infrastructure. Includes deploying enterprise-grade ML systems (e.g., model serving, pipeline automation), integrating data sources, and building dashboards.
• Proficiency in at least one programming language such as Python, Java, or Go, along with solid understanding of data structures and algorithms
• Experience in cross-functional collaboration and leading projects 
• Impact-driven mindset, strong analytical and problem-solving skills, and a continuous passion for learning cutting-edge technologies.
• Proficient in using LLM-powered tools (e.g., Github Copilot, ChatGPT) to boost development productivity

What We’re Looking For (Preferred)

• Industry experience in the MarTech domain, with a strong passion for building customer-centric products
• Strong ownership mindset and architectural thinking, with the ability to lead cross-functional platform initiatives
• Understanding of core ML and deep learning concepts
• Hands-on experience with end-to-end ML workflows and AI system architecture, and familiarity with platforms like Kubeflow, MLflow, or Apache Submarine.
• Familiarity with distributed computing frameworks (e.g., Apache Spark)
• Proficiency with cloud-native ecosystems (e.g., Kubernetes, Helm, Prometheus, Argo Workflows)

#LI-AK1

About Appier

Appier is a leading SaaS company empowering businesses with cutting-edge artificial intelligence (AI) to drive smarter decision-making. Founded in 2012 with a mission to democratize AI, we transform complex data into actionable insights, making AI accessible and profitable. With 17 offices across APAC, Europe, and the U.S., and listed on the Tokyo Stock Exchange (Ticker: 4180), Appier is at the forefront of AI innovation. Visit www.appier.com for more information.

About the Role

We’re on the lookout for an ambitious and technically outstanding Senior Software Engineer, Machine Learning to join our Enterprise Solution Engineering Team, AIXON. This elite team leverages state-of-the-art ML technologies to solve real-world marketing challenges by integrating omnichannel customer data at scale.

In this role, you’ll be the vital bridge between cutting-edge research and production-grade deployment. You’ll design, build, and optimize scalable, high-performance ML infrastructure—including data pipelines, APIs, monitoring systems, and workflow orchestration—that power transformative AI solutions.

What You’ll Do

• Architect and operate resilient ML job execution frameworks covering training, inference, and post-processing workflows.

• Develop and maintain API services and developer tooling to orchestrate ML workflows on Kubernetes using Argo Workflows, Helm, Terraform.

• Build scalable, efficient batch pipelines with Apache Spark to support large-scale ML training and evaluation.

• Design and maintain robust data infrastructures using Trino, Databricks and other modern database technologies, monitored with Prometheus and Grafana for high availability and observability.

• Develop tooling that streamlines ML experimentation, accelerates production workflows, and empowers cross-functional teams to innovate rapidly.

• Collaborate deeply with ML scientists to transform research prototypes into reliable, scalable, user-facing AI products.

• Lead cloud infrastructure design and operations on GCP, leveraging managed services such as Google Compute Engine (GCE) , Google Kubernetes Engine (GKE) , Cloud Storage, Cloud Functions, Cloud Pub/Sub, Cloud SQL, BigQuery, and more.

• Define and implement CI/CD pipelines with tools like Jenkins, Github Action, or ArgoCD to enable seamless, automated deployments.

• Harness distributed computing and parallel programming principles to optimize system resource utilization and performance.

What You Bring

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s degree preferred).

• 5+ years of hands-on experience in ML platform engineering, MLOps, or data infrastructure, deploying enterprise-grade machine learning systems at scale.

• Expert proficiency in Python, Java, or Go, with solid foundations in data structures and algorithm design.

• In-depth experience with cloud environments (AWS or GCP) and cloud-native service management.

• Proven mastery of Docker containers and Kubernetes cluster management, including resource provisioning, autoscaling, and deployment best practices.

• Strong understanding of the ML lifecycle—from training and prediction to evaluation, backtesting, and feedback loops.

• Familiarity with Git workflows and Linux-based development environments.

• Passionate about continual learning and innovation, leveraging AI-powered developer tools like GitHub Copilot and ChatGPT to boost productivity.

What Will Set You Apart

• Experience in the MarTech industry or other customer-centric domains, eager to deliver products that delight users and drive business impact.

• Demonstrated architectural leadership and ownership, skillfully driving complex, cross-team platform initiatives.

• Strong grasp of deep learning fundamentals and end-to-end ML workflow platforms such as Kubeflow, MLflow, or AWS SageMaker.

• Hands-on experience with distributed data processing frameworks like Apache Spark, and pipeline orchestration tools such as Apache Airflow, Argo Workflow, or Luigi.

• Expertise in production-level ML applications, including handling data imbalance, preventing data leakage, and optimizing resource consumption for large-scale training and serving.

• Familiarity with real-time online inference architectures and batch processing trade-offs.

• Enthusiastic adopter of “vibe coding” culture—collaborative, transparent, and always pushing technical excellence together.

• Prior experience building or developing applications related to large language models (LLM), multi-agent LLM systems, or natural language processing (NLP).

Why Join Appier?

At Appier, you’ll stand at the frontier of AI innovation, working alongside world-class engineers and researchers to create products that transform entire industries. Here, your engineering expertise will directly impact millions of users and drive revolutionary advances in marketing technology. If you’re ready to tackle challenging ML infrastructure problems with passion and creativity, Appier is your ultimate playground!

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