Python Developer

LanceSoft, Inc.; Montreal (administrative region); On-site; CAD 90,000 - 120,000; Full time

Job summary

LanceSoft, Inc. is seeking a skilled data/pipeline engineer to work on production-grade data processing systems in Montreal. On-site presence is required 3x per week. The role demands 5-7 years of experience and strong Python capabilities, including FastAPI, SQL, and unit testing in a Unix environment.

You will collaborate in a fast-paced setting, manage multiple projects, and contribute to scalable data solutions in a collaborative team.

Qualifications

• 5-7 years of experience in relevant field.
• Strong proficiency of Python with production-grade data pipelines.
• Familiarity with object-oriented programming (OOP).
• Good knowledge of databases, SQL queries, stored procedures and optimization.
• Expertise in FastAPI for service endpoints and async processing.
• Working knowledge of Unix.
• Version control experience (Git).
• Experience writing unit tests (pytest).

Skills

Python

OOP

SQL

FastAPI

Unix

Git

Unit tests

Tools

pytest

Job description

Location: Montreal (day 1 onboarding onsite/in-office presence required 3x/week)

Years of experience: 5-7 years

Skills Required:

• Strong proficiency of Python with experience developing production-grade data processing pipelines
• Familiarity with object-oriented programming (OOP)
• Good knowledge of Database concepts and writing SQL queries and Stored Procedures and query optimization
• Expertise in FastAPI framework for building service endpoints and asynchronous processing systems
• Working knowledge of Unix
• Experience with version control tools (preferably Git)Writing unit tests (e.g. using pytest)
• Self-starter with ability to work in a fast-paced environment and be able to work on multiple projects

Good to Have:

• Experience of working in Agile Squads
• Finance data domain knowledge
• Understanding of model performance monitoring, model debugging, and logging systems within AI applications
• Experience with containerization and deployment of ML services in enterprise environments
• Experience with anomaly detection algorithms and techniques, particularly isolation forest, clustering, time series analysis, and pattern mining
• Design and deploy generative AI solutions using LLMs and multimodal models to solve business problems
• Expertise in pandas and familiarity in scikit-learn libraries for data manipulation and machine learning model implementation