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

Montreal, Quebec, Canada -

Full Time

Start Date

Immediate

Expiry Date

31 Dec, 25

Salary

0.0

Posted On

02 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Development, AI/ML Technologies, Team Leadership, Python, C#, Go, Java, TypeScript, Data Engineering, Cloud Providers, Kubernetes, MLOps, Microservices, APIs, Machine Learning, Deep Learning, Transformers

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 Lead the development of our AI/ML integration layer team, responsible for delivering AI capabilities to internal product squads and external stakeholders, enabling seamless integration of AI/ML-powered features into our products. This position combines hands-on development with technical leadership. The ideal candidate has a strong background in software engineering, proven experience leading teams, and a solid understanding of AI/ML technologies. You will collaborate with technical and product-focused stakeholders to deliver scalable, reliable, and secure services that bring the latest advancements in AI to production. Responsibilities Build, mentor, and guide a high-performing AI software development team of ; set technical direction, standards, and delivery practices. Own the end-to-end lifecycle of ML/LLM solutions: problem definition, data sourcing and labeling, feature developing, model training/fine‑tuning, evaluation, deployment, and continuous improvement which include : Architecture and delivery of resilient microservices and APIs that power AI features, with strong observability, security, and performance. Designing retrieval‑augmented generation (RAG) and agentic workflows; manage prompt and model versioning, guardrails, and safety policies. Executing hybrid model strategy: integrate third‑party providers and run self‑hosted/open‑source models when cost, privacy, or latency require it. Establishing MLOps foundations: experiment tracking, model registry, feature store, automated training pipelines, CI/CD for models and services, and blue/green or canary rollouts. Implementing online/offline evaluation, human‑in‑the‑loop review, A/B testing, and analytics to validate impact and guide iteration. Ensuring data privacy and compliance (e.g., PHI/PII handling), threat modeling, encryption, access control, and auditability. Collaborate with stakeholders to align roadmaps, prioritize outcomes, and communicate trade‑offs and risks. Qualifications University Degree in Computer Science, Engineering, Mathematics, or a related field—or equivalent practical experience. 10+ years of experience in software development as well, with 3+ years in AI/ML development and several years in team leadership. Demonstrated leadership of development teams delivering AI‑backed features to production with clear business impact. Hands‑on track record building RAG pipelines, evaluation harnesses, and safety/guardrail systems for LLMs. Experience with various model tuning techniques (e.g., SFT, LoRA/QLoRA, DPO/RLHF) Proficiency in Python and at least one additional language (e.g., C#, Go, Java, TypeScript), with strong software design, testing, and CI/CD practices. Experience designing and operating distributed systems and APIs with robust telemetry (metrics, logs, traces) and SLO/SLA thinking. Data engineering fluency: SQL, data modelling, quality checks, and streaming/batch pipelines; familiarity with vector stores and embeddings. Comfortable across major cloud providers and Kubernetes; ability to select managed services vs. self‑hosted stacks based on latency, cost, and privacy constraints. Strong communication and product sense; ability to translate ambiguous problems into iterative, measurable delivery. Depth in machine learning fundamentals (classical ML and deep learning/transformers) and practical model development, tuning, and alignment methods. Nice to Have Background with healthcare or other regulated domains. Experience with Azure and the .NET ecosystem alongside Python. 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 the development of the AI/ML integration layer team, responsible for delivering AI capabilities to internal product squads and external stakeholders. Own the end-to-end lifecycle of ML/LLM solutions, ensuring the architecture and delivery of resilient microservices and APIs that power AI features.