Team Lead, Software Development (AI/ML) at Medfar

Montreal, Quebec, Canada -

Full Time

Start Date

Immediate

Expiry Date

27 Feb, 26

Salary

0.0

Posted On

29 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI/ML Solutions, Technical Leadership, System Design, Collaboration, Problem Solving, Code Review, MLOps Practices, Data Engineering, API Design, Python, C#, Java, Go, TypeScript, SQL, Distributed Systems

Industry

Software Development

Description

Company Description MEDFAR Clinical Solutions was founded in 2010 by two aeronautical engineers who realized that the healthcare system was not exploiting the full potential of technology. Supported by a large community of medical experts and focused on clinical success and patient safety, MEDFAR was the first company to certify a cloud-based Electronic Medical Record in Canada: MYLE (Make Your Life Easy). Committed to promoting excellence and effectiveness in healthcare worldwide, MEDFAR differentiates itself by offering a unique healthcare management solution for clinics, which replaces inefficient processes with a faster and safer technological alternative. Job Description As a Team Lead, Software Development (AI/ML), you will be a key member of our product and platform development teams. You will participate in the architecture, design, implementation and deployment of AI‑powered features and ML/LLM solutions that will support software functionalities developed by our product teams to enrich the ecosystem of products offered by MEDFAR, products that seek to change the healthcare environment by offering new practices and technological innovations. The candidate ideally has experience in developing large‑scale AI/ML‑driven software solutions (including RAG and agentic workflows), leadership and communication skills, as well as a rigorous and analytical mindset with a data‑driven problem‑solving approach focused on measurable business and clinical impact. Main Responsibilities Technical Leadership: Provide technical leadership and mentorship to a high-performing AI/ML-focused software development team, fostering a collaborative, learning-oriented, and innovative environment. Evolve and enforce the standards for code quality, maintainability, and best practices for AI/ML systems and services; ensure adherence to architectural principles, MLOps standards, and coding conventions across models, data pipelines, and APIs. System Design and Development: Design, develop, and implement end-to-end ML/LLM solutions and the microservices/APIs that power AI features, including data pipelines, feature engineering, model training/fine-tuning, evaluation, deployment, and continuous improvement. Collaboration and Communication: Collaborate effectively with cross-functional teams, including product, data, security, and operations, and communicate AI/ML architectural decisions, technical concepts, trade-offs, and project updates to both technical and non-technical stakeholders. Troubleshooting and Problem Solving: Identify and address challenges across the AI stack, including data quality issues, model performance degradation, latency and scalability bottlenecks, and system reliability concerns. Implement effective solutions to ensure optimal model and system functionality, including observability for models and services, robust evaluation and monitoring, and continuous, data-driven iteration on AI features. Code Review and Quality Assurance: Conduct thorough code and experiment reviews to maintain high standards for software and ML quality; collaborate with QA, data science, and engineering teams to define and implement automated testing strategies, evaluation harnesses, and safety/guardrail checks for AI-driven features. Architectural Strategy: Participate in the development and execution of the AI/ML and platform architectural strategy, including RAG and agentic workflows, model lifecycle management, and hybrid model (third-party vs. self-hosted) approaches, ensuring alignment with business goals, compliance requirements, and long-term scalability. Documentation: Create and maintain comprehensive technical documentation, including system and data flows, AI/ML architecture diagrams, model cards, evaluation and safety guidelines, and best practices for developers and stakeholders. Qualifications University degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience. More than 10 years of experience in software development, including several years leading development teams. At least 3 years of hands-on experience designing, building, and deploying AI/ML solutions (including LLM-based systems) into production. Demonstrated track record delivering AI-powered features with measurable business impact, including ownership of end-to-end solution lifecycle. Strong proficiency in Python and at least one additional programming language (e.g., C#, Go, Java, or TypeScript), with solid software design, testing, and CI/CD practices. Practical experience with retrieval-augmented generation (RAG), LLM evaluation and observability, and implementation of safety/guardrail systems. Experience with modern MLOps practices (experiment tracking, model registry, feature store, automated pipelines, and production rollout strategies). Solid understanding of distributed systems and API design, including observability (metrics, logs, traces) and SLO/SLA-oriented thinking. Data engineering fluency: SQL, data modeling, data quality, and working with both batch and streaming pipelines; familiarity with embeddings and vector stores. Knowledge of best security and privacy practices, including handling of sensitive data (e.g., PHI/PII), access control, encryption, and auditability. Ability to work as part of a cross-functional team, mentor others, and collaborate effectively with technical and non-technical stakeholders. Strong communication skills and product sense, with the ability to turn ambiguous problems into iterative, outcome-focused delivery. Ability to communicate fluently in French and in English. Nice to have: Experience in healthcare or other regulated environments, and familiarity with Azure and the .NET ecosystem. Additional Information At MEDFAR, we promote efficiency and excellence in healthcare by offering the most efficient electronic medical record (EMR) on the market. Joining the ranks of MEDFAR means working in a dynamic environment where trust, innovation, quality, and client success guide our days. You decide where you do your best work (at home or at the office) Flexible hours (work-life balance) Generous group insurance coverage as of day 1 of employment Break paid between Christmas and New Years $ 1,500 allocated to you for your professional development Dynamic and multicultural work environment Recruitment Process Virtual Screen with HR - Case Study + Interview - Offer With offices around the world, fluency in both French and English is a must at MEDFAR. Because of the need to communicate with colleagues and/or customers in other provinces or countries, bilingualism enables us to communicate in both languages while promoting the use of French. At MEDFAR, we value diversity, equity and inclusion within our team. We are committed to providing a work environment where every individual feels respected and supported, regardless of their background, identity or abilities.As part of our commitment to a fair and inclusive recruitment process, we offer accommodation to candidates who request it. If you need accommodation during your interview, please let us know so that we can provide you with an adapted experience. MEDFAR has voluntarily subscribed to an Equal Employment Opportunity Program (EEOP). We encourage applications from women, visible minorities, ethnic minorities, aboriginal peoples and people with disabilities. When applying, we invite you to complete this section, which enables us to implement our Equal Employment Opportunity Program (EEOP). Self-identification is not compulsory, but may enable you to benefit from hiring or promotion measures if you have the skills required for the job. To better understand the self-identification process, please consult this guide.

Responsibilities

Lead a high-performing AI/ML software development team and ensure adherence to coding standards and best practices. Collaborate with cross-functional teams to design and implement AI-powered features and troubleshoot challenges across the AI stack.