Celestica

Senior AI Engineer, IT Solutions 1

Celestica$123K — $173K *
Information Technology
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • 11+ years of experience in IT, Software Engineering, or Data Science with a focus on AI/ML development
  • Strong understanding of Generative AI landscapes and vector databases
  • Proven ability to architect end-to-end AI solutions from discovery to deployment
  • Excellent communication skills for conveying complex technical concepts to business leaders
  • Advanced proficiency in Python and relevant libraries
  • Experience with Cloud AI Services like Azure AI Studio or AWS Bedrock (preferred)

Responsibilities

  • Elicit and document technical requirements for AI and Machine Learning projects
  • Define technical feasibility for proposed AI use cases
  • Analyze existing business processes for automation opportunities
  • Design and implement data ingestion pipelines for vector databases
  • Develop, test, and refine AI prompts and orchestration workflows
  • Implement MLOps best practices for CI/CD of AI models
  • Establish monitoring frameworks for model performance in production environments

Benefits

  • Comprehensive benefits package offered
  • Flexible hybrid working arrangement
  • Opportunity to work in a supportive and innovative team environment
  • Access to the latest AI tools and technologies
  • Opportunity for ongoing professional development and learning
Full Job Description
Req ID: 137430
Remote Position: Hybrid
Region: Americas
Country: Canada
State/Province: Ontario
City: Toronto

Summary

We are seeking a highly motivated and technically proficient AI Engineer to join our growing Data & Analytics team. In this role, you will be a key liaison between business stakeholders and the technical AI team, translating complex business challenges into scalable artificial intelligence and machine learning solutions. You will be responsible for defining technical requirements, designing AI architectures (including Generative AI and RAG patterns), and collaborating with the Data Center of Excellence to deliver high-quality, production-ready AI tools that drive innovation and operational efficiency across the organization.

Detailed Description

AI Solution Scoping & Requirements:
  • Elicit and document technical requirements for AI and Machine Learning projects through workshops and deep dives with stakeholders across various departments.
  • Define the technical feasibility of proposed AI use cases, identifying appropriate model architectures (LLMs, SLMs, or traditional ML) and success metrics (Accuracy, F1-score, Perplexity, etc.).
  • Analyze existing business processes to identify automation opportunities and areas where Generative AI can provide a competitive advantage.


Data Engineering & AI Pipeline Design:
  • Work with stakeholders to identify and prepare high-quality datasets for model training, fine-tuning, and grounding.
  • Design and implement data ingestion pipelines for vector databases, ensuring data integrity and optimal embedding strategies for Retrieval-Augmented Generation (RAG).
  • Collaborate with data engineers to ensure scalable, secure, and compliant data flows between enterprise systems and AI models.


Model Development & Orchestration:
  • Develop, test, and refine AI prompts and orchestration workflows using frameworks like LangChain, LlamaIndex, or Semantic Kernel.
  • Evaluate and select appropriate foundation models (OpenAI, Anthropic, Llama, etc.) based on performance, cost, and latency requirements.
  • Translate business logic into technical specifications for API integrations, model endpoints, and user interfaces.


MLOps, Deployment & Monitoring:
  • Implement MLOps best practices to ensure the continuous integration and deployment (CI/CD) of AI models.
  • Establish monitoring frameworks to track model performance, "drift," and hallucination rates in production environments.
  • Ensure AI solutions adhere to corporate data governance, security, and ethical AI principles.


Knowledge/Skills/Competencies

  • Essential Skills:
    • 11+ years of experience in Information Technology, Software Engineering, or Data Science, with a significant focus on AI/ML development.
    • Strong understanding of Generative AI landscapes, including LLMs, prompt engineering, and vector databases (e.g., Pinecone, Weaviate, Milvus).
    • Proven ability to architect end-to-end AI solutions from discovery to production deployment.
    • Excellent communication skills, with the ability to explain complex technical AI concepts to non-technical business leaders.
    • Advanced proficiency in Python and relevant libraries (NumPy, Pandas, PyTorch, or TensorFlow).
    • Experience with Cloud AI Services (Azure AI Studio, AWS Bedrock, or Google Vertex AI [Preferred]).

    Desirable Skills:
    • Knowledge of SQL and advanced data modeling for structured and unstructured data.
    • Familiarity with MLOps tools (MLflow, Kubeflow) and containerization (Docker, Kubernetes).
    • Experience working in an Agile/Scrum development environment.
    • Knowledge of AI security frameworks and responsible AI practices (e.g., OWASP for LLMs, MCP).
    • Industry experience in manufacturing or a related industrial sector.


Physical Demands

  • Duties of this position are performed in a normal office environment.
  • Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data. Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required.


Salary

The stated range includes Base Salary and target Short-Term Incentive (STI) compensation only. A comprehensive benefits package is offered in addition to this range.

The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.

Salary Range: $123,200 - 173,200 CAD

Typical Experience

  • 11+ years of progressive experience in technical roles, with at least 3-5 years specifically focused on AI/ML engineering or architecture.
  • Proven track record of delivering production-grade AI applications.
  • AI-related certifications (e.g., Azure AI Engineer Associate, AWS Machine Learning Specialty) are highly preferred.


Typical Education

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field; or a robust combination of work experience and specialized AI certification.


Notes

This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.

About Celestica

Celestica is a Canadian multinational electronics manufacturing services company headquartered in Toronto, Ontario. The company provides a range of services to original equipment manufacturers (OEMs) in the aerospace and defense, communications, enterprise computing, healthcare, industrial, semiconductor, and smart energy industries. Celestica's services include design and engineering, supply chain management, assembly and testing, and after-market services. The company operates in North America, Europe, and Asia and has manufacturing facilities in over 10 countries. Celestica was founded in 1994 as a subsidiary of IBM Canada and became an independent company in 1997.
Learn more about Celestica
Size
23,915 employees
Market Cap
$1.3 billion
Industry
Founded
1994
5 Year Trend
-1.3%
NASDAQ

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