LLM/ML Engineer

Posted 14 Hours Ago
Be an Early Applicant
Athens
Junior
Artificial Intelligence • Fintech • Information Technology • Productivity • Software • Conversational AI • Generative AI
Aisera: ChatGPT and AI Search for the Enterprise
The Role
The LLM/ML Engineer will develop and deploy advanced AI/ML models, collaborate with teams to meet project requirements, design scalable algorithms, and evaluate model performance. Responsibilities include coding, maintaining documentation, and staying updated on AI/ML technologies.
Summary Generated by Built In

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.

LLM/ML Engineer

We are looking for a highly skilled Junior LLM/ML Engineer (~2 years professional experience) to join our team and help drive our AI and ML initiatives, including LLM finetuning, hybrid Search and NLP for dialog agents, to new heights. If you are passionate about AI/ML, knowledgeable about the latest developments, especially in LLMs, and have a track record of academic and professional excellence, we want to hear from you!

This role will be based in Greece and is fully remote.

Responsibilities:

  • Develop and deploy state-of-the-art AI/ML models and solutions.
  • Collaborate with cross-functional teams, including product managers, software engineers, and data engineers, to understand and follow project requirements, and task deliverables.
  • Design and implement scalable and efficient AI/ML algorithms and models.
  • Evaluate and select appropriate, state of the art AI/ML techniques, algorithms, and libraries to meet task requirements. 
  • Write code of high quality using solid engineering principles. 
  • Evaluate quality, performance, and accuracy of AI/ML models through rigorous testing and validation processes.
  • Maintain detailed documentation of your task outcomes, including systems and algorithms.
  • Develop and maintain a deep understanding of emerging technologies in AI/ML.

Basic and Additional Qualifications:

  • Minimum of 18 months of professional experience in AI/ML engineering
  • Excellent knowledge of AI/ML algorithms, techniques, and basic frameworks, such as TensorFlow and PyTorch.
  • Good knowledge with GenAI and LLM models and architectures.
  • Solid understanding of data science principles and best practices, including data preprocessing, feature engineering, and model evaluation.
  • Proficiency in Python development for AI/ML tasks.
  • Excellent problem-solving and analytical skills.
  • Communication and interpersonal skills, with the ability to communicate complex concepts to technical stakeholders.
  • Ability to work effectively in a fast-paced, collaborative environment.
  • Master's degree in Computer Science, Engineering, Data Science, or a related field; PhD preferred
  • Some experience with Search Engine and Information retrieval algorithms and techniques is preferred.


Top Skills

Python
The Company
HQ: Palo Alto, CA
265 Employees
On-site Workplace
Year Founded: 2017

What We Do

Aisera is a leading provider of enterprise Generative AI apps and a platform that helps enterprises accelerate revenue growth, improve user productivity, lower costs, and create magical user experiences.

Our products - AiseraGPT, AI Copilot, AI Search, and Agent Assist - are built on our Generative AI Platform that serves as the fundamental building block for enterprise GenAI applications. Aisera leverages a TRAPS framework (Transparent, Responsible, Auditable, Privacy, and Secure) to meet stringent data governance requirements while adhering to the highest standards of Responsible AI.

Aisera products deliver human-like interactions with a multi-modal interface, providing contextually rich conversations that boost user productivity. With pre-trained, domain-specific LLMs grounded in customer data, our products offer higher accuracy, fewer hallucinations, and increased resolution rates. They address critical industry challenges, spanning a wide range of solutions, including AI-driven software engineering, code generation, content and knowledge creation, workflow automation, and natural language AI-powered analytics.

AiseraGPT automates knowledge retrieval and repetitive tasks, while AI Copilot serves as a personal companion for answering questions, analyzing data, and completing tasks. Agent Assist provides real-time assistance for agents, including case summarization, recommendations, and next best actions, through an embedded UI widget in SaaS applications like ServiceNow, Salesforce, Workday, and more. Aisera’s AI Search allows users to perform secure, private, and permissions-aware enterprise-wide searches using natural language, generating answers, summaries, and micro-actions to boost efficiency.

Aisera provides a Universal Bot with a unified interface to resolve user requests across all domains, including Engineering, HR, IT, Sales, Marketing, Customer Service, Life Sciences, Healthcare, Financial Services, and Retail. Aisera compliments these offers with action bots that are built-in with customizable AI Workflows through an Event and Visual Studio to take action and automate business processes.

Aisera technology is based on an Agentic and reasoning architecture that can perform intentless and intent-driven natural language requests across unstructured and structured databases, business apps, and systems of records. Users benefit from a default large context window, personalized responses, and summarizations.

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