Machine Learning Engineer - Client: National Safety Services (Full Time Perm) - Remote
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Contract
- Experience
- 5+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- Completion of a Degree or Masters in Computing Science, Machine Learning, Engineering, or a related technical discipline, or an equivalent combination of education and experience
- 5+ years of relevant experience in machine learning engineering, software engineering, applied AI, or a related technical role
- Experience with ML/AI solutions from prototype/pilot through MVP and into production
- Strong understanding of the broader technical infrastructure required to support ML applications, including platforms, cloud services, systems, APIs and data pipelines.
- Ability to communicate architecture, technical trade-offs, resource requirements and risks clearly to senior leadership and non-technical stakeholders
- Strong programming skills, particularly in Python, with experience using relevant ML frameworks, libraries and development tools
- Demonstrated ability to independently lead technical projects, troubleshoot complex problems and make sound technical decisions with limited oversight
- Experience working with cross-functional subject matter experts and translating business or domain requirements into practical technical solutions
- Comfortable working in an early-stage or growing technical environment where systems, processes and infrastructure are still being established
- Experience supporting or mentoring technical team members and contributing to the growth of an engineering or ML function is considered an asset
- Must be legally eligible to work in Canada
Full description
About The Role
If you’re excited to build a technology team and platform from the ground up and help bring an occupational health and safety organization into the AI and digital space, this Machine Learning Engineer opportunity is for you!
As a special service for this engagement, Amii is supporting the recruitment process for this position on behalf of our client, National Safety Services Inc. (NSS). The successful candidate will be employed directly by NSS and will not be an Amii team member.About Our Client
National Safety Services Inc. (NSS) is a Canadian consultancy and technology company specializing in occupational health and safety (OHS). With over 200 years of combined industry experience, NSS supports private and public sector organizations in achieving regulatory compliance, reducing risk exposure, and improving operational safety. Their multidisciplinary team delivers services ranging from program audits and risk assessments to training and competency framework design. NSS is now leveraging AI and machine learning to modernize traditional safety management systems and disrupt the contractor management space with scalable, intelligent solutions.
National Safety Is Committed To, And Relies Upon, Their Core Values In Guiding Their Business Decisions, Partnerships, And Talent Selection. All Team Members Are Expected To Exemplify The Following Core Values
Integrity - We value authentic, transparent connections.
Collaboration - Stronger together through collaboration.
Resilience - Meeting adversity with a positive mindset.
Growth Minded - Curious, life-long learners driven to improve.
Respect - We believe that everyone deserves respect.
Required Skills / ExpertiseKey Responsibilities
- Lead the completion, implementation and deployment of AI/ML solutions from prototype through MVP to production, ensuring seamless integration with the broader technology platform and adaptability for new clients
- Design, develop and deploy LLM-powered applications using Python, LLM APIs (OpenAI, Gemini or similar) and frameworks such as LangChain or LangGraph, including RAG, embeddings, vector search and document processing pipelines
- Define and evolve the technical architecture and technology stack required to support the organization's AI products, making decisions on platforms, tools, services and system integrations to support long-term scalability
- Design, build and maintain scalable technical infrastructure using REST APIs (FastAPI or similar), SQL, PostgreSQL, vector databases, Docker and cloud platforms (AWS, Azure or GCP)