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Senior AI​/ML Engineer

Job in Calgary, Alberta, D3J, Canada
Listing for: Socket.dev
Full Time position
Listed on 2026-08-03
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 175000 CAD Yearly CAD 175000.00 YEAR
Job Description & How to Apply Below

Velir is an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. As of 2023, Velir acquired Brooklyn Data Company, a premier data and analytics consultancy focused on leadership, process improvement, implementation, and advanced analytics.

At Velir, we believe people are our greatest asset. Our culture is built on a foundation of trust, collaboration, and continued improvement. We strive for excellence in everything we do, embracing challenges as opportunities for growth. Our success is driven by a shared passion for making a positive impact on our customers, our communities and each other. We are a remote first company that offers competitive pay and excellent benefits.

Overview

Senior AI/ML Engineers are senior individual contributors who design, build, and deploy production-grade AI/ML systems for both client-facing and internal products. They partner with leadership and cross-functional teams to translate business needs into scalable ML and LLM-based solutions.

This role does not typically include direct reports but requires strong technical leadership, mentorship, and influence across teams.

Responsibilities AI/ML System Design & Leadership
  • Lead the design and implementation of scalable ML systems, including supervised, unsupervised, and LLM-based solutions
  • Translate research and prototypes into production-ready systems
  • Partner with stakeholders to identify high-impact AI/ML opportunities and define optimal technical approaches
  • Provide technical mentorship and contribute to team upskilling
LLM & Production AI Systems
  • Build and operate LLM pipelines, including prompt design, fine-tuning, and evaluation
  • Develop RAG-based systems using embeddings, vector stores, and retrieval strategies
  • Design evaluation frameworks, feedback loops, and datasets to continuously improve model performance
  • Create reusable tooling to accelerate experimentation, deployment, and monitoring
MLOps & Deployment
  • Own end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and iteration
  • Establish best practices for reproducibility, observability, CI/CD, and model versioning
  • Partner with platform/Dev Ops teams to ensure reliability and scalability
  • Promote responsible AI practices, including governance, fairness, and transparency
Cross-Functional Collaboration
  • Lead cross-functional initiatives across data engineering, analytics, and AI/ML
  • Translate complex ML concepts into clear recommendations for technical and non-technical audiences
  • Collaborate with clients and internal teams to plan and deliver AI/ML solutions
  • Contribute documentation, frameworks, and shared best practices
Project Execution
  • Scope and lead complex AI/ML initiatives aligned to business outcomes
  • Align stakeholders and drive execution across teams
  • Establish clear success metrics and ensure delivery of high-impact solutions
Skills & Qualifications
  • 5–7 years of experience in ML engineering, AI engineering, or related fields, with production deployment experience
  • Strong programming skills in Python and SQL; experience with PyTorch and Hugging Face
  • Experience building LLM applications, including RAG, embeddings, and vector search
  • Experience with cloud platforms (AWS or Azure; e.g., Sage Maker, Bedrock, Azure ML)
  • Strong understanding of ML fundamentals: data design, training, evaluation, and experimentation
  • Familiarity with LLM alignment techniques (e.g., SFT, DPO, RL)
  • Experience with MLOps practices: CI/CD, monitoring, retraining, and experiment tracking
  • Proficiency working with complex, multi-source datasets and defining evaluation strategies
  • Strong software engineering fundamentals (testing, modularity, code review)
  • Experience mentoring engineers and influencing technical direction
  • Strong communication skills with both technical and non-technical stakeholders
Tech Stack
  • Languages: Python, SQL
  • Frameworks: PyTorch, Hugging Face
  • Platforms: AWS, Azure, Snowflake, Databricks
Physical Requirements
  • Frequent sitting at a desk performing work on a computer
  • Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions
Compensation Range: $175, annually

Please…

Position Requirements
10+ Years work experience
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