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Lead AI Research Engineer

Iris.ai

Iris.ai

Software Engineering, Data Science
Spain
Posted on Tuesday, November 14, 2023

IRIS.AI is an ML driven software that helps scientists and researchers all over the world throughout their work. We are building a fully fledged Science Assistant Machine that can read and understand scientific text and give you the full picture of the current state-of-the-art in a human understandable way.

Our AI facilitates our clients’ research and development process in creation of innovative, sustainable resources, overcoming global food, health and climate crises, while driving education and science.

 

Job Description:

The expansion of our tools portfolio is driving the need and possibility for conducting fundamental research in-house at Iris.ai. Because of that we are looking for a driven, curious and excited to work in a startup Lead Research Engineer to join and manage our team of researchers. The work will consist of conducting fundamental research (reading and implementing scientific articles) on the topics listed in our website , converting existing research scripts into application ready libraries and  writing scientific technical reports and articles to be submitted to conferences and peer-reviewed journals. 

Technologies used:

  • Python OOP
  • Python ML/NLP libraries, such as tensorflow, pytorch etc.
  • AWS
  • Docker
  • Open AI API
  • Git

Job Responsibilities:

  • Research and Development: Lead AI research engineers are responsible for conducting cutting-edge research in the field of artificial intelligence. This includes staying up to date with the latest developments in AI and machine learning, and using this knowledge to develop innovative solutions.
  • Algorithm Development: Design, implement, and optimize machine learning algorithms and models for specific applications. This involves data preprocessing, feature engineering, model selection, and fine-tuning.
  • Prototyping: Develop prototypes and proof-of-concept models to demonstrate the feasibility of AI solutions for various use cases.
  • Project Management: Define project objectives, scope, and deliverables. Manage project timelines, allocate resources, and monitor progress to ensure that projects are completed on time and within budget.
  • Data Collection and Annotation: Supervise data collection and annotation efforts, which are crucial for training and evaluating machine learning models.
  • Model Evaluation: Design experiments and metrics to evaluate the performance of AI models. Continuously iterate on models to improve their accuracy and robustness.
  • Technical Documentation: Prepare detailed documentation of research findings, algorithms, models, and code for internal and external use.
  • Collaboration: Collaborate with cross-functional teams, such as software engineers, data scientists, and domain experts, to integrate AI solutions into products or services.
  • Ethical Considerations: Consider the ethical implications of AI solutions and ensure responsible and fair AI practices in research and development.
  • Resource Allocation: Manage computational resources, including cloud infrastructure and hardware, to support AI research and development.
  • Quality Assurance: Implement best practices for testing and quality assurance to ensure that AI models and software meet high standards of performance and reliability.
  • Stay Informed: Keep abreast of the latest advancements in AI and attend conferences, workshops, and seminars to network with peers and contribute to the AI community.
  • Publications: Contribute to the generation of intellectual property through publications in relevant journals and conferences.
  • Strategic Planning: Work with senior management to align AI research initiatives with the organization's strategic goals and mission.
  • Problem Solving: Tackle complex technical challenges, identify bottlenecks, and find innovative solutions to advance AI research and development.
  • Team Caring and Leadership: Lead, mentor and support a team of AI researchers, juniors and interns, providing guidance, setting project goals, and ensuring smooth and successful execution. 
Requirements:
  • PhD degree in Machine Learning, Computer Science or similar subject
  • At least 5 years of relevant industry ML research experience
  • Experience of leading and managing a team of ~5 people
  • Professional experience with ML and NLP projects
  • Knowledge and experience with Natural Language Processing
  • Impeccable coding skills in Python
  • Knowledge in object oriented programming, code optimization, parallel programming, and architecture design
  • A record of publications in the ML or NLP fields.
  • Naturally caring for teammates
  • Located in Europe
LIFE AT IRIS OFFERS:Job Value 
  • A job with immense value - global mission, changing the course of Science 
  • A futuristic mix of AI , Engineering and Science
  • An international team of Aces - highly intelligent and versatile engineers + experienced entrepreneurs
Compensation Package
  • Competitive salary
  • Annual Salary Review 
  • Share options plan
Work-Life  Balance 
  • 30 days annual paid vacation + bonus days. Yes, for real!
  • Flexible work hours 
  • Flexible work location - You choose where to work from within Europe
  • 100% remote work - You want it? - You have it!
  • Regular Team building activities and travels 
  • Seasonal Working Get Togethers (summer / winter) 
  • Personal  equipment reimbursement program 
  • Charity and volunteer activities
  • Employee Recognition program
Professional Development
  • Career Enhancement plan
  • Knowledge transfer
  • New Technologies Introduction & Learning opportunities 
  • Mentorship opportunities 
  • Workshops, Conferences, Hackathons (internal & external) 
  • Freedom to bring innovation and your ideas to life 

If you believe you have what it takes to join a team working on the frontier of Text Understanding, Argument Mining and Topic Modelling, and work on building our next generation of ML driven tools, please do not hesitate to apply.