Eleks is seeking an AI/ML Architect to lead the design, development, and operationalization of scalable artificial intelligence and machine learning systems across the organization. This role blends deep hands-on technical expertise with strong architectural thinking to guide technology selection, shape AI strategy, and ensure high-quality delivery.
What You'll Do
- Design end-to-end AI/ML architectures, including data ingestion pipelines, feature stores, model training, deployment patterns, and monitoring frameworks.
- Lead the evaluation and selection of AI/ML tools, frameworks, cloud components, and platforms.
- Define standards, best practices, and governance frameworks for responsible AI usage.
- Partner with product and engineering leadership to shape the long-term AI roadmap.
- Provide expert guidance across the full ML lifecycle: data preparation, modeling, experimentation, optimization, deployment, and monitoring.
- Architect scalable solutions using Python-based ML stacks and modern cloud environments.
- Support the development of LLM-based applications, vector database architectures, and retrieval-augmented generation (RAG) systems.
- Evaluate new AI capabilities, such as agent frameworks, fine-tuning strategies, and MLOps automation.
- Oversee the technical design of AI projects and ensure solution quality, reliability, and security.
- Work with cross-functional teams to define clear success metrics for AI initiatives.
- Conduct architecture reviews, code reviews, and technical deep dives.
- Mentor engineers and data scientists to elevate technical excellence.
What We're Looking For
- 7+ years of experience in data science, machine learning, or AI engineering.
- 3+ years in a senior or principal-level architectural role.
- Strong proficiency in Python and common ML/AI frameworks like TensorFlow, PyTorch, Scikit-Learn, and transformers libraries.
- Hands-on experience with Cloud AI services such as AWS Sagemaker, Azure ML, or GCP Vertex AI.
- Hands-on experience with Data engineering tools including Spark, Databricks, Airflow, and Kafka.
- Hands-on experience with LLM architectures, fine-tuning, embeddings, and vector stores like FAISS, Pinecone, or Weaviate.
- Hands-on experience with MLOps tools such as MLflow, Kubeflow, DVC, and CI/CD pipelines.
- Solid understanding of distributed computing, APIs, microservices, and containerization with Docker and Kubernetes.
Technical Stack
- Languages & Core Frameworks: Python, TensorFlow, PyTorch, Scikit-Learn, transformers libraries
- Cloud AI: AWS Sagemaker, Azure ML, GCP Vertex AI
- Data Engineering: Spark, Databricks, Airflow, Kafka
- LLM & Vector Stores: FAISS, Pinecone, Weaviate
- MLOps: MLflow, Kubeflow, DVC
- Infrastructure: Docker, Kubernetes
Team & Environment
You will collaborate closely with data engineers, ML engineers, software developers, product teams, and business stakeholders.
Benefits & Compensation
- Close cooperation directly with customers.
- Challenging and intellectually stimulating tasks.
- Opportunities for continuous competence development.
- Work in a team of dedicated professionals.
- A dynamic environment with a low level of bureaucracy.
Work Mode
This role operates in a local-country mode, based in Canada.
Eleks is an equal opportunity employer.
