MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- ML Ops Engineer supporting the operational lifecycle of AI-powered products at Achievers. Leading initiatives within a high-performing team in a hybrid work environment from Toronto.
Responsibilities
- Lead high-impact initiatives that shape how millions of people experience work around the world
- Bring your unique perspective to complex and challenging projects - apply your expertise in data science, influence technical direction, and share your knowledge with fellow team members
- Join a close-knit, no-ego, high-performing team that solves meaningful problems and celebrates successes together
- Work alongside an experienced leadership team who is genuinely invested in your career growth
- Thrive in a fast-paced, high-growth environment where innovation is encouraged and your voice truly matters
- Deploy and operate ML models and LLMs using Vertex AI, Cloud Run, and GKE
- Automate packaging, versioning, and release of models, prompts, embeddings, and related artifacts
- Design scalable inference architectures (sync, async, agentic), including batching and GPU/TPU autoscaling
- Build and maintain ML and GenAI workflows using Vertex AI Pipelines, Cloud Composer (Airflow), or custom orchestration
- Implement CI/CD for ML code and GenAI artifacts (prompts, fine-tuned models, evaluation suites)
- Schedule retraining, re-embedding, and re-indexing to ensure model freshness
- Manage and version prompts, system instructions, RAG components, and agent workflows
- Operationalize fine-tuned or custom models using Vertex AI tuning capabilities
- Implement logging, lineage, and metadata using Vertex ML Metadata and Cloud Logging
- Partner with data scientists, GenAI engineers, product managers, and engineers to deliver production-ready ML systems
Requirements
- Experience in MLOps, ML platform engineering, or cloud-based AI infrastructure
- Strong hands-on experience with GCP, especially Vertex AI (ML & GenAI), BigQuery/BigQuery ML, Cloud Run or GKE, and Cloud Composer
- Strong Python skills with experience in testing, CI/CD, containerization, and infrastructure automation (Terraform)
- Experience with LLM workflows: embeddings, vector databases, prompt engineering, and evaluation
- Exposure to agentic workflows and frameworks such as MCP
- Familiarity with Vertex AI Model Garden, tuning, monitoring, and vector search technologies
- Exposure to LLM safety, moderation, or red-teaming workflows
- Strong communication and cross-functional collaboration skills
- Detail-oriented, reliability-focused mindset
- Comfortable working in fast-evolving environments
- Strong sense of ownership and accountability
Benefits
- Rewards for your impact through our Recognition and Rewards program
- Health Benefits and Life Insurance Coverage beginning on your first day
- Parental Leave Top-up
- Employer matched RRSP contributions
- Flexible Vacation to recharge, so you can bring your best
- Employee and Family Assistance Program offering mental health, legal, and financial counselling
- Supported professional development and career growth (Linkedin Learning, mentorship)
- Employee-Led Employee Resource Groups that celebrate our diversity
- Regular events designed to build connection, belonging, and well-being
- Hybrid flexibility, with time in our beautiful Liberty Village, Toronto office
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