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. Salary range is 75-140K euros based on experience and qualifications.

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.