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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