AI Jobs

Education Requirements:

• MSc in a quantitative field (Computer Science, Statistics, Software/Information System Engineering or similar), specializing in Machine Learning

Experience Requirements:

• 2+ years of working experience as a data scientist

• Hands-on experience with Python development

• Strong knowledge with SQL/NoSQL databases

• Experience in deploying ML algorithms to production environments

Other Requirements:

• Deep understanding of machine learning models and statistical inference

• Great communication and interpersonal skills

• Experience with Recommender System, Reinforcement learning or AutoML will be an advantage

• Experience with one or more deep learning framework will be an advantage

Responsibilities:

• Lead end-to-end ML projects (exploration to deployment)

• Take part in developing new cutting-edge algorithms based on various ML techniques

• Improve ML pipeline

• Work in a short life-cycle research and development environment

• Work closely with Product, Customer Success, BI, Dev and DevOps teams

Experience Requirements:

• 6+ years Backend development, designing and implementing micro-services

• 2+ years Python in Linux environment

Other Requirements:

• Excellent communication and collaboration abilities

• Experience with NoSQL and SQL databases

• Experience working with Messaging Queues

• Good knowledge of AWS services

• Good knowledge of containerization technologies

Responsibilities:

• Collaborate with cross-functional teams to design, develop, and deploy robust and scalable features

• Architect, implement, and optimize backend solutions using Python

• Collaborate with product managers, data scientists, tech-leads

• Enhance the performance, scalability, and security of the platform

• Stay up-to-date with industry trends and emerging technologies

Experience Requirements:

• 3+ years Linux System Administration

Other Requirements:

• Excellent communication and collaboration abilities

• Strong expertise in AWS

• Experience with installation and maintenance of different NoSQL Databases and middlewares

• Deep knowledge of containerization technologies

• Proficiency in scripting and automation tools

Responsibilities:

• Develop and implement a cloud-native strategy

• Lead efforts to manage container orchestration platforms

• Enhance and automate CI/CD pipelines

• Drive the adoption of IAC principles and tools

• Collaborate closely with software engineers

Education Requirements:

• B.Sc. or higher in Computer Science or similar

Experience Requirements:

• 15+ years of experience developing backend systems with passion for excellence

• 10+ years of experience in Python

• 5+ years of experience with tools such as containers, CI/CD, testing / monitoring / logging

• Experience with REST APIs, server-side API integration, queues and distributed systems

• Knowledge of ORM, SQL and Data Modeling

Responsibilities:

• Help us build a world class scalable backend platform

• Responsible for the end-to-end feature lifecycle: starting from design and architecture, through implementing, testing, and releasing the feature

• Take part in architecture design and technological leadership

Education Requirements:

• B.Sc. or higher in Computer Science or similar

Experience Requirements:

• 10+ years of experience developing backend systems with a passion for excellence

• 5+ years of experience in Python

• 5+ years of experience with tools such as containers, CI/CD, testing/monitoring / logging

• Experience with REST APIs, server-side API integration, queues, and distributed systems

• Knowledge of ORM, SQL, and Data Modeling

Responsibilities:

• Help us build a world class scalable backend platform

• Responsible for the end-to-end feature lifecycle: starting from design and architecture, through implementing, testing, and releasing the feature

• Take part in architecture design and technological leadership

Education Requirements:

• BSc./MSc. In CS or similar – an advantage

Experience Requirements:

• 5+ years experience as a Machine Learning Engineer

• 10+ years of experience with Python/Java/Scala

• Strong understanding of distributed systems, object-oriented programming and design patteri

• Distributed Compute frameworks such as Spark, Dask, Ray etc

• Hands-on experience designing, training, and deploying machine-learning models

Responsibilities:

• Work on pecans’s core data and machine learning infrastructure

• Create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation

Education Requirements:

• BSc./MSc. In CS or similar – an advantage

Experience Requirements:

• 10+ years experience as a Machine Learning Engineer

• 15+ years of experience with Python/Java/Scala

• Strong understanding of distributed systems, object-oriented programming and design pattern

• Distributed Compute frameworks such as Spark, Dask, Ray etc

• Experience with REST APIs, server-side API integration, queues and distributed systems

Responsibilities:

• Work on pecans’s core data and machine learning infrastructure

• Create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation

Education Requirements:

• Bsc in a relevant field

Experience Requirements:

• 5 years of experience as a data scientist working on tabular data

• Proficient in Python, SQL, and Spark

• Experience in creating measurable value with ml (defining KPI’s, designing AB tests, monitoring)

• Experience with time series

• Experience with AWS / Databricks – advantage

Responsibilities:

• Work at the forefront of the data world, optimizing predictive models and assisting our clients to use those predictions to affect their business

• Continuously helping our clients achieve their business goals, and reinforce the value of Pecan’s modules, and the ease of use of our platform

• Handle complex data science challenges using state-of-the-art techniques such as custom loss-functions, auto-encoders, embeddings, LSTM, and many more