Let's start with the role

As a Principal Data Scientist, you will play a critical role in leveraging data and AI to make decisions in real time to deliver the right reward and message to the right customer at the right time and medium. and create a competitive advantage for the organization The ideal candidate will be a tenured Data Scientist, ML or AI engineer that has a proven track record of designing and implementing cutting-edge, real-time and AI-empowered applications along with the corresponding ML/DL algorithms.
As a Principal Data Scientist you will:
Architecture: Design scalable, reliable and high-performance AI applications along with their corresponding ML/DS algorithms.
Innovation: Set the tech direction in the AI tribe in order to deliver state-of-the-art AI models in production.
Mentorship: Inspire and mentor fellow data scientists, fostering technical and soft skill growth.
Pioneering: Stay ahead of the AI curve, applying emerging technologies to enhance our capabilities, disrupt the industry and showcase what’s truly possible.
Strategic Planning & Prioritization: Define the company-wide AI technical and product roadmap, in-line with the business product roadmap. Resist the AI hype and enable impact-driven prioritization with quick and impactful PoCs that demonstrate the value.
Autonomy & end-to-end Ownership: From ideation, to translation of business needs to technical requirements, all the way to operationalization and maintenance, demonstrate autonomy on high-complexity and ambiguous projects and ownership of the outcome.

What you’ll bring

Must have:
8+ years of hands-on experience leveraging large-scale data to build ML/DS models with Python
PhD-level expertise in one or more of the following domains: Recommendation Systems,,Time-series, Reinforcement Learning, Graph Learning
A deep understanding of the ML development lifecycle and how to optimize the trade-offs in each step. 
Proven track record of designing, implementing, optimizing and scaling performant AI-empowered applications. Solid experience with MLOps and quality evaluation practices in order to operationalize and maintain those applications in production.
Excellent communication and collaboration skills targeting a diverse audience from stakeholders to cross-functional technical teams, in order to provide technical guidance and insight.

Nice to have:
Expertise in constraint optimization, uplift modeling. causal inference & personalization 
Exposure to a variety of domains especially CRM and a diverse family of models. 
Familiarity with a wide range of big data technologies, such as Apache Spark, Delta Lake, Apache Kafka, Apache Flink and NoSQL databases.

We're looking for an AI expert who wants to be at the forefront of innovation in the iGaming industry. Join us in shaping the future of iGaming with breathtaking experiences that thrill and delight players around the world.

Kaizen Gaming Perks

• 🕑 Hybrid way of working & remote options
• 🏃 A buddy will support you with your onboarding
• 💸 Competitive pay and bonus scheme
• 👩‍⚕️ Private health insurance for you and your family
• 💰 Monthly meal allowance 
• ⭐Developmental 360° feedback framework
• 📚 Unlimited access to Udemy & continuous training
• #li-ap1

Let's start with the role

At Kaizen, we strive to harness the power of modern AI algorithms to continuously improve our product and business. Kaizen’s AI department consists of product, platform and research teams and lies at the core of that mission. We develop AI products for various applications, ranging from detection of fraudulent activity to personalized gaming recommendations and from AI-powered co-pilots to CRM optimizations. 

We structure our teams to be self-driven, autonomous, and cross-functional. Within these teams, you will have the opportunity to work with Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, Product Owners and Agile Delivery Leads.

As a Senior Machine Learning Software Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models. 

• Collaborate closely with data scientists in order to deliver production-ready model training pipelines;
• Design scalable solutions in a distributed environment;
• Design scalable inference pipelines and architectures;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimization and scalability;
• Develop and maintain internal tools and libraries;
• Write CI/CD/CT pipelines.

What you’ll bring

• Extensive experience in software development using Python in large scale, high-performance production environment;
• Significant hands-on experience in designing ML software systems;
• Significant experience with cloud environments like Microsoft Azure or AWS;
• Solid understanding of:
• The ML project lifecycle;
• MLOps concepts and tools such as MLflow or Kubeflow;
• ML algorithms and models.

• Hands-on experience with Spark and PySpark;
• Excellent problem solving and communication skills.

#Machine Learning (ML) #MLOps #AIOps #Software Engineering

Kaizen Gaming Perks

• 🕑 Hybrid way of working;
• 🏃 A buddy will support you with your onboarding;
• 💸 Competitive pay & bonus scheme;
• ⭐Developmental 360° feedback framework;
• 💰 Monthly meal allowance;
• 👩‍⚕️ Private health insurance for you and your family;
• 📚 Unlimited access to Udemy & continuous training;
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-EL1

Let's start with the role

At Kaizen, we strive to harness the power of modern AI algorithms to continuously improve our product and business. Kaizen’s AI department consists of product, platform and research teams and lies at the core of that mission. We develop AI products for various applications, ranging from detection of fraudulent activity to personalized gaming recommendations and from AI-powered co-pilots to CRM optimizations. 

We structure our teams to be self-driven, autonomous, and cross-functional. Within these teams, you will have the opportunity to work with Data Scientists, Machine Learning Engineers, Data Engineers, Data Analysts, Product Owners and Agile Delivery Leads.

As a Senior Machine Learning Software Engineer, you will focus on delivering robust and scalable Machine Learning pipelines and you will support the operationalization of Machine Learning models. 

• Collaborate closely with data scientists in order to deliver production-ready model training pipelines;
• Design scalable solutions in a distributed environment;
• Design scalable inference pipelines and architectures;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimization and scalability;
• Develop and maintain internal tools and libraries;
• Write CI/CD/CT pipelines.

What you’ll bring

• Extensive experience in software development using Python in large scale, high-performance production environment;
• Significant hands-on experience in designing ML software systems;
• Significant experience with cloud environments like Microsoft Azure or AWS;
• Solid understanding of:
• The ML project lifecycle;
• MLOps concepts and tools such as MLflow or Kubeflow;
• ML algorithms and models.

• Hands-on experience with Spark and PySpark;
• Excellent problem solving and communication skills.

#Machine Learning (ML) #MLOps #AIOps #Software Engineering

Kaizen Gaming Perks

• 🕑 Hybrid way of working;
• 🏃 A buddy will support you with your onboarding;
• 💸 Competitive pay & bonus scheme;
• ⭐Developmental 360° feedback framework;
• 💰 Monthly meal allowance;
• 👩‍⚕️ Private health insurance for you and your family;
• 📚 Unlimited access to Udemy & continuous training;
• 👨‍👩‍👧‍👦 Family Support.
• #LI-Hybrid
• #LI-EL1

How You'll Make an Impact: 

As a Senior DevOps Engineer at Cloudbeds, your goal is to constantly improve and scale our SaaS platform to deliver an exceptional experience to hoteliers and their guests worldwide. You'll own the creation, monitoring, automation, and support of our cloud infrastructure and delivery pipelines — enabling product teams to ship high-quality software with speed and confidence. Working within a bottom-up culture that values healthy debate and collaborative problem-solving, you'll have real influence over architecture decisions and the opportunity to shape how we scale infrastructure for one of the fastest-growing hospitality technology platforms in the world.

Our Infrastructure Team: 

Our Infrastructure team is made up of engineers who take genuine pride in their craft, owning projects end-to-end and holding themselves to a high bar. We're passionate about technology and constantly pushing to improve our stack, not just maintain it. If you thrive in an environment where attention to detail matters, great communication is a given, and you're comfortable challenging the status quo to make things better, you'll feel right at home here.

What You Bring to the Team:

• Architect, improve, and scale Cloudbeds' cloud infrastructure on AWS, with a focus on reliability, security, and performance
• Build and evolve our Kubernetes (EKS) platform, driving adoption of containerization best practices across engineering teams
• Automate infrastructure provisioning and configuration using infrastructure-as-code tools like Terraform
• Design, build, and maintain CI/CD pipelines (GitHub Actions, ArgoCD) that enable fast, reliable software delivery
• Partner with product and engineering teams to drive projects to production, sharing DevOps expertise and ensuring strong environment configuration from the infrastructure side
• Maintain and improve monitoring, logging, and alerting systems to ensure platform health and rapid incident response
• Participate in on-call rotation to support production environment stability.

What Sets You Up for Success:

• 5+ years of experience as a DevOps Engineer working hands-on with AWS (networking, compute, storage, databases, queues, cache, permissions).
• 5+ years of strong Kubernetes and Docker experience, including implementing and scaling EKS platforms at production scale.
• Deep expertise with Terraform for infrastructure-as-code and configuration management.
• Proven experience building and supporting CI/CD pipelines using GitHub Actions and ArgoCD.
• Strong knowledge of monitoring and observability tools such as Datadog, Prometheus, Loki, or AWS CloudWatch.
• Working knowledge of web application servers (NGINX, Ingress controllers), databases (MySQL, PostgreSQL, Aurora), caching (Redis, Memcached), and queue technologies (SQS).
• Ability to write Bash and/or Python scripts to automate operational tasks.
• Strong Linux system administration skills and solid networking fundamentals.
• Excellent written and verbal English communication skills; comfortable working asynchronously across a globally distributed remote team.

#LI-REMOTE #LI-IK1

What We Do: AI Service Management (AISM):

Aisera offers the world's first AI-driven service experience solution that automates operations and support for IT, Sales and customer service, making businesses and customers successful by offering consumer-like self-service resolutions to users. Aisera fast tracks the digital transformation journey with user and service behavioral intelligence that drives end-to-end automation of tasks, actions, and business processes. Aisera is a top-tier, VC-funded startup headquartered in Palo Alto, Calif. and a strategic partner with AWS, Microsoft Azure, Google Cloud, ServiceNow and Salesforce.

Aisera has received numerous recognitions, including the following: Forbes AI50; CNBC Upstart 100 Top Startup; Gartner Cool Vendor; Red Herring Top 100 Global Innovator; CIO Innovation Startup Award; CIO Review Top ITSM Solution; Aragon Research Hot Vendor; TiE50 Startup Award; and Silicon Review 50 Most Admired Companies.

The Role: 

Lead AI/ML research and development initiatives while growing as a software engineer. Drive machine learning innovation with strong research acumen while building production-ready ML systems. Partner with AI Systems Tech Lead for technical mentorship and system integration.

Key Responsibilities:

• Lead ML research, experimentation, and development from concept to deployment
• Design and implement novel ML/AI approaches, staying current with cutting-edge research and methodologies
• Architect ML pipelines, training infrastructure, and model evaluation frameworks
• Guide ML engineering decisions including model selection, feature engineering, and optimization strategies
• Translate academic insights into practical applications
• Mentor junior ML engineers and establish ML best practices across the team
• Work closely with AI Systems Tech Leads to ensure delivery of optimized AI systems and services to production
• Enforce data governance and privacy: Follow processes and implement methods that ensure data governance, privacy, and security. 
• Collaborate with cross-functional teams: Work closely with product managers, and other stakeholders to ensure the AI/ML solutions align with the organization's goals and objectives.
• Communicate effectively: Clearly document your work and effectively communicate your findings, insights, and recommendations to both technical and non-technical stakeholders, fostering a collaborative and informed environment.

Required Expertise:

• 5+ years in ML engineering with demonstrated advanced development or research capabilities (innovative projects, publications, theses)
• Advanced degree in AI/ML or related subjects with relevant undergraduate degree
• Deep understanding of ML fundamentals: deep learning, statistical modeling, optimization, and evaluation methodologies
• Strong Python skills with ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face)
• Experience with ML experiment tracking, model versioning, and reproducible research practices
• Ability to translate research papers into working implementations
• At least a year of leadership experience driving technical ML initiatives for a small team
• Solid foundation in software development practices (testing, version control, code review)

Growth Opportunities:

• Opportunity to lead both research direction and technical implementation
• Direct involvement in productionizing cutting-edge ML research
• Accelerated software engineering development 

Preferred (in order):

• Background in NLP 
• Experience with distributed training, MLOps, and cloud ML platforms
• Track record of research publications or open-source ML contributions
• Enterprise SaaS experience 

This role is in a Product-building AI/ML team. This is a Greece-based, full-time, employee-status, fully remote position. 

Aisera is Global and our success draws upon the diverse viewpoints, skills and experiences of our employees. We are proud to be an equal opportunity employer and are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or veteran status.