Who we are

We’re a thriving and agile tech development firm. People are at the center of everything we do. Simply put, we care. Our team personally cares about our clients and the world around them, and we care about our team’s life-long dreams, aspirations, and career development.

We strongly believe in the power of community. This is why we seek opportunities to build meaningful relationships with everyone around us.

We celebrate diversity in all its forms. Backgrounds, personalities, career paths, languages... you name it. We actively innovate, learn, and share stories around the topic. We want everyone to feel welcomed and included in all we do.

We like having fun and enjoying ourselves. We wake up every day inspired to build a more efficient and enjoyable world.

Role Overview As a Senior Software Developer with strong Data Engineering and MLOps experience, you design, build, and deliver robust data and machine learning solutions for our clients. You combine solid software engineering habits with hands‑on experience in data pipelines, cloud environments, automation, model deployment, monitoring, and production‑ready ML systems.

You’re comfortable moving between backend development, data engineering, ML lifecycle practices, infrastructure, CI/CD, observability, and technical leadership. You collaborate closely with technical and non‑technical teammates, mentor others, and help teams make sound technical decisions as we deliver enterprise‑grade AI and data solutions.

The technologies below are a reference point for our stack. Above all, we hire for strong fundamentals, judgment, ownership, and growth potential.

Your Key Responsibilities

Design, build, and deliver scalable software, data,



and machine learning solutions for client projects

Identify solutions to cross‑functional problems using your software development, data engineering, and MLOps experience

Design, plan, and implement data pipelines, ML workflows, and supporting cloud or on‑premise infrastructure

Develop end‑to‑end solutions aligned with specifications and documentation

Build and improve CI/CD pipelines, data pipelines, model deployment workflows, and automation practices

Contribute to containerized, virtualized, and cloud‑native environments that support data and ML workloads

Support modernization initiatives by improving architecture, testing, deployment, observability, data quality, and maintainability

Define, document, and communicate non‑functional requirements such as performance, reliability, security, scalability, and maintainability

Support ML lifecycle practices such as experiment tracking, model versioning, validation, deployment, promotion, rollback, and monitoring

Coach colleagues on software development, data engineering, MLOps, and delivery best practices

Take initiative, own deliverables end‑to‑end, and manage priorities effectively

Uphold and strengthen software development guidelines and quality standards

Research, test, and implement new techniques, tools, and technologies





Advise clients on technical direction, trade‑offs, architecture, data platforms, and ML solution design

The ideal candidate

5+ years of software development experience, including recent hands‑on experience with data engineering, MLOps, or production ML systems

Bachelor’s degree, college degree, certification in a software‑related field, or equivalent experience

Intermediate or conversational French at a minimum

Strong backend development experience

Strong technical judgment and ability to make pragmatic architectural decisions

Experience building or supporting data pipelines, data platforms, or ML deployment workflows

Experience collaborating directly with clients or stakeholders

Ability to mentor teammates and help raise the quality of technical delivery

Comfortable working in ambiguous environments and bringing structure to complex problems

You should be proficient with

At least one major cloud platform such as AWS, Azure, or Google Cloud

At least one major server‑side programming language such as Python, Java, Node.js/TypeScript, Go, C#, or similar

At least one major data engineering platform such as Databricks, Snowflake, BigQuery, Microsoft Fabric, or similar

Backend development, API design, and distributed systems

Data pipeline orchestration, version control, data validation, feature pipelines, or feature stores

ML lifecycle practices such as experiment tracking, model versioning, validation, deployment, promotion, rollback, and monitoring

CI/CD pipelines and deployment automation

Infrastructure as code and provisioning tools such as Terraform, CDK, CloudFormation, Bicep, Ansible, or

📌 Senior Software Developer, Data (Montreal)
🏢 Osedea
📍 Montreal