Machine Learning Engineer - Client: National Safety Services (Full Time Perm) - Remote

Machine Learning Engineer - Client: National Safety Services (Full Time Perm) - Remote

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 / Expertise

Key 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)
• Implement MLOps/DevOps practices, including CI/CD pipelines, workflow orchestration tools (Apache Airflow or similar), automated testing, monitoring and maintenance to ensure reliable and secure production AI applications
• Collaborate with occupational health and safety subject matter experts to translate complex regulatory and business requirements into practical AI-powered solutions for compliance assessments, document analysis, risk identification and gap analysis
• Independently lead technical projects, evaluate emerging technologies, troubleshoot complex challenges and establish engineering standards and best practices while communicating technical decisions and risks to senior leadership
• Support the growth of the organization's technical team by identifying future engineering needs, collaborating with external contractors and technical partners, and contributing to hiring, onboarding, mentorship and technical leadership as the function expands

Required Qualifications:

• 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

Non-Technical Requirements:

• Desire to take ownership of a problem and demonstrate leadership skills
• Interdisciplinary team player enthusiastic about working together to achieve excellence
• Capable of critical and independent thought
• Able to communicate technical concepts clearly to senior non-technical stakeholders
• Intellectual curiosity and the desire to learn new things, techniques and technologies

Applicants must be legally eligible to work in Canada at the time of application.