Benefits:

• Competitive salary and equity options package

• Hybrid Working

• Regular in-person gatherings, free lunch options, office snacks and happy hours

• Comprehensive health and wellness package (medical, dental, vision, life insurance, disability, mental health)

• PTO, maternity leave, baby bonding leave

Benefits:

• Competitive salary and equity options package

• Hybrid Working

• Regular in-person gatherings, free lunch options, office snacks and happy hours

• Comprehensive health and wellness package (medical, dental, vision, life insurance, disability, mental health)

• PTO, maternity leave, baby bonding leave

Benefits:

• Competitive salary and equity options package

• Hybrid Working

• Regular in-person gatherings, free lunch options, office snacks and happy hours

• Comprehensive health and wellness package (medical, dental, vision, life insurance, disability, mental health)

• PTO, maternity leave, baby bonding leave

Benefits:

• Competitive salary and equity options package

• Hybrid Working

• Regular in-person gatherings, free lunch options, office snacks and happy hours

• Comprehensive health and wellness package (medical, dental, vision, life insurance, disability, mental health)

• PTO, maternity leave, baby bonding leave

Benefits:

• Employee Stock Options

• Extensive Health Insurance Coverage

• Team Outings

• Delicious Meals and Snacks at the Office

• Generous Leave and Paid Time Off Policies

Education Requirements:

• Graduate degree in computer science or related field

Experience Requirements:

• Strong knowledge of theoretical and practical aspects of machine learning, including probability, statistics, learning theory, algorithms, and software architecture.

• Proven ability to deliver machine learning-driven solutions, particularly in production environments.

• Experience in Python programming for machine learning projects, with a solid understanding of CI/CD pipelines and deploying models using AWS or other cloud platforms.

• Good understanding of applied machine learning concepts, with experience in deploying ML models as microservices; previous experience with Conversational AI or NLP projects is a plus

Other Requirements:

• 2+ years of industrial experience

• Atleast 1 year of experience in Data Science or Machine learning (NLP/Speech would be preferable)

Responsibilities:

• Building ML models on our core ML platform; and monitor, diagnose and maintain active deployments.

• Create and own technical design for ML models associated with the voice-bot.

• Own the ML metrics related to bots - Intent, SCR, resolution, etc. and responsible for continuous improvement of ML performance

• Define and drive quality, performance, robustness, and reliability of our deliveries by collaborating with delivery stakeholders.

• Drive and organize research, discussion and reviews towards continuous improvements of our models and capabilities

Benefits:

• Employee Stock Options

• Extensive Health Insurance Coverage

• Team Outings

• Delicious Meals and Snacks at the Office

• Generous Leave and Paid Time Off Policies

Experience Requirements:

• Strong knowledge of SQL

• Working knowledge of scripting (one of Python, R)

• Experience working with at least 1 BI Tool (Superset, Tableau, Metabase, Google Analytics, Clevertap, MixPanel etc.)

• Strong communication skills - ability to effectively communicate the insights developed to the various stakeholders in the organization

• Able to work with agile product development teams and able to identify new ways to help your team be effective

Other Requirements:

• Brownie points to folks who’ve built or worked on analyzing conversational AI products

• Experience working on Machine Learning and NLP systems

Responsibilities:

• Support the product and delivery teams to drive improved product quality and customer satisfaction by leveraging data to study business and UX impact for features and product improvements

• Deep dive into data and identify right problem statements and right segments to target and take experimentation driven product delivery approaches.

• Work closely with Tech, Product, CS and Delivery to deliver standard and custom dashboards to enable understanding of bot health and performance with minimal guidance

• Capture insights from customer feedback, experiments, research, and data analysis to identify trends and pinpoint the drivers behind them; translate these insights into tactical solutions to improve our voicebot deliveries

• Becoming the domain champion of the product/function with a clear data-driven understanding of how callers interact with our voicebot

Benefits:

• A chance to grow within a leading, fast-moving AI company

• A competitive compensation package with equity shares

• A diverse and friendly environment

• Social and company events

• Startup offices in central Oslo

Education Requirements:

• Master's degree or higher in Electrical Engineering, Computer Science, or a related field

Experience Requirements:

• Hands-on experience with (audio) signal processing

• 2+ years of industry experience in applying machine learning to real-world problems

• Experience using development using software engineering best practices, including code reviews, continuous integration, and tooling for development environments

• MLOps experience. E.g., scaling training in cloud environments, model versioning, and model performance profiling

Other Requirements:

• Excellent problem-solving and communication skills

Responsibilities:

• Develop and optimize machine learning algorithms for real-time audio enhancement

• Research improvements in machine learning models for audio

• Build, administer, and scale ML processing pipelines

• We believe in end-to-end ownership; this role will involve taking ML models from development to production at scale

Education Requirements:

• PhD or Master's in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent fields

Experience Requirements:

• Experience in ML/AI product development and iterative work

• Experience in general programming languages: Python, C++, Java, R.

• Experience working with any of the following machine learning frameworks / libraries- sklearn, tensorflow, Pytorch, numpy, scipy, spacy

• Preferred experience within NLP and semantic technologies with understanding of fundamental linguistic and grammatical concepts and their use in NLP applications

• Experience with research communities and/or efforts, including having published papers (being listed as author) at NLP field

Other Requirements:

• 3+ relevant work experience, including internships, full time industry experience or as a researcher in a lab

Responsibilities:

• Develop and maintain NLP algorithms, language models and pipelines for English Edu applications.

• Rapidly prototype and build production ready solutions

• Improve and develop machine learning models using state-of-the-art techniques within deep learning.

• Participate in all team activities such as planning, design discussions and reviews, and usability sessions

• Identify the right user experience so that the output of your ML workflows can be integrated and be easily interpretable for, and actionable by, the business users

Benefits:

• Career Growth

• Remote-First

• Unlimited PTO

• Health benefits (medical, dental, vision)

• Paid family leave

Benefits:

• Career Growth

• Remote-First

• Unlimited PTO

• Health benefits (medical, dental, vision)

• Paid family leave

Benefits:

• Generous 401(k) plan with matching

• Comprehensive premium health, dental, and vision insurance for you and your dependents

• Early exercise provisions of equity options

• Unlimited PTO

• Healthy lunch and dinner options catered daily at our offices

Education Requirements:

• Bachelor’s degree or International Equivalent in Computer Science, Mathematics, Physics, Information Science or related field

Responsibilities:

• Defining the project and its objective

• Researching and reproducing state-of-the-art methods

• Formulating new algorithmic ideas

• Prototyping these ideas and testing them via carefully designed systematic experiments

• Transferring successful ideas to production in collaboration with platform engineering teams

Benefits:

• Work for a company with an impactful mission

• Early-stage startup, plenty of opportunities to grow and develop

• Flexibility with remote work

• Compensation includes equity

Education Requirements:

• Master’s degree in Computer Science or another relevant field

Experience Requirements:

• Proven experience in building end-to-end complex AI-based systems

Other Requirements:

• Strong software development skills and attention to detail when building modular code in Python

Responsibilities:

• Design, develop, and implement end-to-end AI solutions

• Research, prototype, and apply the latest discoveries and methods in AI

• Make a significant impact on our product

Education Requirements:

• Bachelor’s degree in computer science, mathematics, physics or equivalent

Experience Requirements:

• Experience on NLP experience (topic modeling, sentiment analysis and classification, text mining), preferably with translation technologies

• Passion for new Artificial Intelligence advancements such as GPT3

• Experience writing Python code and using libraries such as PyTorch, TensorFlow, Scikit-learn or Numpy

• Ability to work independently and cross-functionally to deliver production-ready systems that meet the needs of our customers

Responsibilities:

• Working with a small team of engineers, designers, and data scientists to ideate, design, and build a new product.

• Experimenting with new techniques to improve our transcreation algorithms.

• Thinking creatively to propose new methods of boosting the quality of the transcreated campaigns.

• Adapting the models to adjust to the requirements of different publishing platforms.

• Mentoring your teammates, creating opportunities for their growth, and fostering a collaborative culture

Benefits:

• Potential for stock options

• Dynamic, agile work environment

• Forefront of AI and Security innovation

• Flexible hybrid work arrangement

• Healthy work-life balance

Experience Requirements:

• Proven expertise in LLMs and multi-agent approaches, including code generation

• Strong knowledge of prompt engineering techniques

• Proficiency in Python and experience using machine learning and AI frameworks

• Data mining knowledge

• Strong understanding of AI ethics

Other Requirements:

• Prior publications in conferences and journals (a plus)

• Excellent problem-solving skills

• Ability to work in a fast-paced startup environment

• Fluency in English (additional languages a plus)

Responsibilities:

• Implementing, integrating, benchmarking and deploying AI models for vulnerability detection

• Fine-tuning, testing, and optimizing models

• Collaborating with engineering and security researchers

• Collecting and analyzing datasets

• Contributing to the scalability and efficiency of AI

Responsibilities:

• Conducting research and developing algorithms for computer vision and machine learning.

• Implementing and testing algorithms on real-world data.

• Working with the engineering team to integrate algorithms into products and services

Benefits:

• Real world project experience: work on difficult & bleeding edge research problems, at scale

• Job opportunities: Subsequent fulltime or internship consideration

• Networking opportunities: access to internal events and introductions

Other Requirements:

• We do not accept talent agency submissions for this role

Responsibilities:

• Contribute to our models research or open source repos

• Developer relations: write documentation, give workshops, build demos & integrations

• Community building: coordinate events, support users

Benefits:

• We pay an “all-in” pay and you will cover your own insurance/medical from the amount

• 14 days leave (and unlimited sick days)

• Annual equipment budget (once 2 month probation has been completed)

Experience Requirements:

• Strong conceptual or mathematical understanding

• Experience with LLMs, including popular foundation models like llama, or Qwen

• [Bonus] Experience with Training LLMs beyond LORA/RAG

• [Bonus] Experience with software or hardware optimization techniques, e.g. flash attention

• [Bonus] Experience running LLMs in production (e.g. Triton Inference Server, etc)

Responsibilities:

• Train and fine-tune foundational LLM models

• Work with multiple modalities from vision to speech

• Push out insightful knowledge to the greater research & open source community

• Collaborate with engineers to productize research milestones

Benefits:

• We pay an “all-in” pay and you will cover your own insurance/medical from the amount

• 14 days leave (and unlimited sick days)

• Annual equipment budget (once 2 month probation has been completed)

Experience Requirements:

• Strong conceptual or mathematical understanding

• Experience with LLMs, including popular foundation models like llama, or Qwen

• Experience with Training LLMs beyond LORA/RAG

• Experience with software or hardware optimization techniques, e.g. flash attention

• [Bonus] Experience running LLMs in production (e.g. Triton Inference Server, etc)

Other Requirements:

• [Bonus] Expertise in Vision, Speech, and Robotics domains

Responsibilities:

• Train and fine-tune foundational LLM models

• Work with multiple modalities from vision to speech

• Push out insightful knowledge to the greater research & open source community

• Collaborate with engineers to productize research milestones

Experience Requirements:

• Experience with finetuning large language models

• 2+ years of experience working directly with large language models

• Deep knowledge of machine learning frameworks such as Pytorch and Deepspeed.

• Strong background in programming languages such as Python and C++

• Entrepreneurial spirit and willingness to adjust to dynamic customer needs

Other Requirements:

• Desire to grow quickly by going above and beyond expectations

Responsibilities:

• Design and run experiments on how to best finetune our in-house LLM models.

• Deploy these custom models end-to-end alongside our ML engineering team.

• Build new MLOps tools from 0 > 1 inside our existing platforms.

• Work closely with leadership and customers to understand large-scale recruiting and HR pain points, and develop state-of-art machine learning solutions for them.

• Write production ready code with speed, cost, and usability in mind