Senior Software Engineer, Machine Learning (Enterprise Solution)

Reposted Yesterday
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Taipei City, TWN
In-Office
Senior level
Artificial Intelligence
The Role
Design, build, and operate scalable ML infrastructure and data pipelines for enterprise marketing solutions. Develop API servers, orchestrate ML jobs on Kubernetes, implement Spark batch pipelines, ensure observability with Prometheus/Grafana, and collaborate with ML scientists to productionize research into product features.
Summary Generated by Built In

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

Skills Required

  • Bachelor's degree in Computer Science, Engineering, or related field
  • 3+ years practical experience in ML platform engineering, MLOps, or data infrastructure
  • Proficiency in at least one programming language such as Python, Java, or Go and strong data structures and algorithms understanding
  • Experience deploying enterprise-grade ML systems (model serving, pipeline automation), integrating data sources, and building dashboards
  • Experience with Kubernetes and orchestration tooling (Argo Workflows, Helm) and infrastructure as code (Terraform)
  • Experience designing and scaling batch ML pipelines (Apache Spark)
  • Experience with relational databases such as PostgreSQL and monitoring/observability tools (Prometheus, Grafana)
  • Experience in cross-functional collaboration and leading projects; strong analytical and problem-solving skills
  • Proficiency using LLM-powered developer tools (e.g., GitHub Copilot, ChatGPT) to improve productivity
  • Master's degree in a related field
  • Industry experience in MarTech and customer-centric product development
  • Understanding of core ML and deep learning concepts and end-to-end ML workflows
  • Familiarity with ML platforms like Kubeflow, MLflow, or Apache Submarine
  • Strong ownership mindset and architectural thinking for platform initiatives
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The Company
HQ: San Francisco, CA
642 Employees
Year Founded: 2012

What We Do

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 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.

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