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
Senior Machine Learning Engineer building causal and decision systems for CSC Generation’s consumer businesses. Developing pricing and other commercial automation using experimentation, uncertainty, and policy learning.
Senior Deep Learning Engineer developing player - tracking, evaluation, and forecasting models for SumerSports’ football intelligence platform. Driving research threads into production for NFL and NCAA teams.
Machine Learning Specialist developing AI, models, and analytical data products for the Government of Alberta. Applying machine learning to improve public services and policymaking.
Machine Learning Engineer developing production AI models and scalable MLOps platforms for Wave, which helps small businesses thrive. Collaborating on financial - risk applications, governance, observability, and reliable deployment.
Senior Geospatial ML Engineer building satellite - imagery vegetation intelligence for a climate - tech company. Improving production models and pipelines to help utilities prevent wildfires and outages.
Senior Machine Learning Engineer building scalable recommender systems for Thomson Reuters’ legal, tax, compliance, government, and media platforms. Implementing secure ML products and infrastructure.
ML Engineer scaling Torc Robotics’ simulation platform for autonomous trucks. Embedding with Autonomy teams to operationalize replay, recompute, metrics, visualization, and model integrations.
Senior ML Engineer building production AI services and MLOps platforms for Hyatt, a global hospitality company. Optimizing cloud - based inference, infrastructure, and model operations.
Machine learning engineer developing real - time underwriting models for Affirm’s buy - now - pay - later platform. Productionizing risk systems, feature pipelines, monitoring, and experimentation workflows.