152 Predictive Models jobs in Canada

Job Description: Salary: Maximum fee of $35,000 Request for Proposals Freshwater Literature Review and Data Analysis Commencing for October 2025 to March 2026 18 July 2025 PROPOSAL DEADLINE: Monday, September 8 by 5pm EDT PROPOSALS DELIVERED TO: Wildlife Conservation Society Canada 1.0 Background Wildlife Conservation Society (WCS) Canada is a national non-governmental organization with a mission is to save wildlife and wild places in Canada through science, conservation action, and by inspiring people to value nature. WCS Canada is affiliated with global WCS programs in more than 60 countries, and we are active at the science-policy interface in Canada and internationally. This RFP is issued by WCS Canadas Ontario Northern Boreal program, active since 2004 in the far north. As one of the few organizations with a continuous scientific presence in the region, we lead field-based research on large mammals, freshwater fish, and peatlands; co-develop programs with First Nations; collaborate with academic, government, and Indigenous researchers; and contribute to policy development to guide conservation decisions. 2.0 Contracting opportunity WCS Canada producing a report summarizing multiple years of freshwater ecological data that has been collected on the water quality, water chemistry, fish contaminants, and benthic invertebrates in northern boreal rivers in Ontario. We are seeking proposals (RFP) from qualified individuals or groups to support the completion of this report. We are requesting that individuals or groups submit a proposal outlining their qualifications, relevant experience, and proposed approach to conducting a literature review and statistical analyses of previously collected data. This work will inform and support the creation of a comprehensive and useful summary report by WCS Canada that outlines the status and trends in these northern boreal rivers. 3.0 Proposal Administration All requests for clarification and questions concerning this RFP must be submitted in writing no later than 5 September 2025 via email to Brianna Kim, Finance and Administrative Manager (indicate Freshwater Literature Review and Data Analysis on the subject line). Responses, if determined appropriate by WCS Canada, will be issued in writing to all known proposers. Proposals, plus attachments, are to be submitted in e-form to: Brianna Kim, Finance and Administrative Manager, WCS Canada may request an interview of any proposer (vendor). Such a request for an interview does not constitute a contract award. Proposals must be received no later than 5:00 PM, 8 September 2025 Key Dates:Last day to submit questions 7 September 2025 Proposals due8 September 2025 Interviews of proposers 11 to 18 September 2025 Notice of Award by 25 September 2025 4.0 Scope of Services and Desired Qualifications The services and deliverables to be provided by the proposer: Freshwater data analyses:Conduct an analysis of the spatial and temporal patterns of previously-collected data on fish contaminants, water quality, water chemistry, and benthic invertebrates in XXX (geography of the data analysis from watersheds over X years; andWhere applicable, compare findings to appropriate benchmarks and reference data from other relevant regions or studies; andProvide a clear interpretation of the data, supported by the freshwater literature review (below).Freshwater literature review:Conduct a focused review of both formally-published, peer-reviewed literature and grey literature (e.g., government reports, technical memos, unpublished studies) related to fish contaminants, water quality, water chemistry and benthic invertebrates from northern boreal river systems. The review should prioritize sources that directly inform or contextualize the interpretation of the collected data; andOrganize identified literature into a database that includes a summary for each resource.Provide assistance and support for summarizing the literature review and data analyses into a final report to be written by WCS Canada staff. The selected proposer is expected to have the following qualifications: Must have experience with freshwater ecological monitoring and research, including familiarity with common approaches used for: freshwater ecological monitoring, freshwater statistical analyses, and freshwater literature reviews;Additional preference will be given for experience with ecological monitoring and research in northern boreal rivers;Must be familiar with ecological analyses in R; andBe familiar with WCS Canadas mission and programmatic activities. 5.0 Length of Engagement The term of engagement is for an approximately 6-month period ending March 30, 2026. 6.0 Proposal Content Proposals should be clear and concise and should address in detail, and with appropriate documentation, each of the items listed below. WCS Canada may request clarification of any proposal during the evaluation process, but is not bound to do so, and proposers should not assume they will have any further opportunity to clarify their proposals subsequent to the proposal due date. Each proposer is requested to submit, on or before the submission deadline, a package containing its proposal addressing the following items in the order listed: A. Technical Qualifications 1. Contact Information On a single cover sheet, please provide:Contact information for the lead individual(s) who are anticipated to work on the project, including e-mail addresses, telephone number, and street address.Web address (if relevant).Year proposer was established (if relevant).Size of proposer (if relevant).List of proposed staff assigned to this project (if relevant).Signature of Principal and date of the signature. 2. Overview (1-page maximum) Proposers should provide a summary of their understanding of the services and deliverables that will be their responsibility and a description of the methods they will use to achieve those objectives, including technical quality assurance, and general management practices for comparable projects. 3. Qualifications Proposers are requested to provide detailed information that demonstrates the following:Experience providing the services requested in this RFP;Proficiency with projects of comparable size and complexity; andDemonstrable commitment to diversity and inclusion of staff and subcontractors. 4. Timetable/Schedule Proposers should produce a draft schedule that outlines critical milestones for the work. 5. Resume(s) A resume/CV of the individual(s) proposing to conduct the work should be attached, which must outline and explain the relevant experience of the individual(s) with similar previous projects. Upon award of the contract, substitutions of personnel will not be allowed without the prior written consent of WCS Canada. 6. References Proposers are requested to provide examples of up to three (3) similar projects, recently completed or in progress, with the following information for each:Description of the workName of a contact person who can provide a reference References may be contacted directly by WCS Canada. B. Fee Proposal Maximum Fee The total proposal fee shall not exceed $5,000 CAD, inclusive of all applicable sales taxes, administrative expenses, and any other project-related costs.Base fee ___Additional fees (e.g., information technology infrastructure costs, administrative support charge) ___ Total ___ 3.Other services Provide information regarding how any requested additional services will be charged (e.g., personnel with titles and hourly or per diem rates). 7.0 General Conditions of Proposal Submissions The following general conditions apply to all proposals submitted in response to any RFP issued by WCS and WCS Canada (collectively referred to below as (WCS Canada):Non-Binding: WCS Canadas solicitation of proposals in response to any RFP does not commit WCS Canada to award a contract, and this RFP is not an offer to enter into a contract for the services to be provided as described herein.Proposal Materials and Costs: WCS Canada is not liable for any costs incurred in the preparation, submission or negotiation of a response to its RFP or incurred for any other purpose or reason in connection with the RFP. No materials submitted with this RFP will be returned.Confidentiality: All information and material contained in any WCS Canada RFP or issued by WCS Canada or any of its agents as part of any WCS Canada RFP process is confidential and is the exclusive property of WCS Canada.Modifications: As a condition of award, WCS Canada may request any proposer to make revisions, additions, or deletions to its proposal.Subcontractors: After award of contract, WCS Canada will have no obligation, financial or otherwise, to any subcontractor of the awardee. Nevertheless, any subcontract will be required to be subject to and consistent with the prime contract between WCS Canada and the awardee, and WCS Canada may require any subcontract to include specific terms and conditions.Reserved Rights: WCS Canada at any time in its sole discretion may, without notice and without liability to any proposer or any other party for their expenses incurred in the preparation of the responses hereto or otherwise, do any and all of the following:Amend or withdraw this RFP;Accept or reject any and all proposals received in response to this RFP;Award the contract to a proposer other than the proposer offering the lowest fee;Request additional materials and clarification or modification of any submitted proposal;Extend the time for submission of all proposals after notification to all prospective proposers;Terminate negotiations with a selected proposer and select another proposer;Take such action as WCS Canada deems appropriate if negotiations fail to result in a signed agreement within a reasonable amount of time; and/orTerminate or modify the solicitation and selection process at any time and re-issue the solicitation to whomever WCS Canada deems appropriate. The selected vendor will be required to execute a written agreement with WCS Canada, including terms generally consistent with those set forth in Appendix A hereto, effective upon the date the written agreement is executed by both WCS Canada and the selected vendor. 8.0 Evaluation and Selection Criteria Selection Process:WCS Canada will review and evaluate all proposals to determine each proposer's rating. This evaluation may include a request to interview proposers and for proposers to virtually present their proposals for purposes of clarification.The proposal offering the most advantageous terms based on the criteria below will be selected for the award. WCS Canada may reject any and all proposals if, in its sole opinion, no proposal satisfies its criteria. Evaluation Criteria: The evaluation criteria and weight will be as follows: Demonstrated technical capability to provide the services (50%);Project-related experience (25%); andClient references (25%) APPENDIX A CONTRACT, INSURANCE, AND REGULATORY REQUIREMENTS 1. Payment Contractor will submit invoices for its work, in a form acceptable to WCS Canada, to its contact for review, who will submit the invoices for payment. Payment is subject to acceptance of the services. Contractor will be paid without deductions for income taxes or other sums which employers in Canada are required to deduct from employees wages. Even though income tax and other deductions are not made by WCS Canada, Contractor should be aware that WCS Canada may be obligated by Canadian regulations to report to Canada Revenue Agency total annual amounts paid to Contractor. Contractor will be solely responsible for the payment of all withholding and other taxes, of whatever type or nature, arising out of or related to its engagement under this Agreement and agrees to and hereby does indemnify and defend WCS Canada and its directors, officers, employees, independent contractors and agents against any claim relating to such taxes. WCS Canada will pay approved fees and expenses within thirty days after receipt of acceptable documentation. 2. Relationship of the Parties Contractors relationship to WCS Canada under this Agreement is that of an independent contractor. Nothing in this Agreement will be deemed to constitute a relationship of employer-employee, joint venture, partnership, agency, or legal representative between Contractor and WCS Canada for any purpose. Neither Contractor nor any of its employees, independent contractors or agents will receive the health insurance, sick leave, vacation, pension, retirement savings plan or other fringe benefits, or severance or termination pay, associated with regular employment at WCS Canada. 3. Termination Either party may terminate this Agreement without cause by furnishing at least 30 days written notice to the other. In such event, Contractor will be paid only for services actually rendered to the date of termination. With reasonable cause, either party may terminate this Agreement immediately upon written notice to the other. Contractor shall not incur any additional expenses between the date of notice of termination and the date of termination without the prior written consent of WCS Canada. 4. Confidentiality Contractor warrants that it will maintain in strict confidence WCS Canadas Confidential Information (as defined below) to which it has access during the term of this Agreement. Contractor will treat WCS Canadas Confidential Information with the same standard of care that it uses in maintaining its own Confidential Information, provided that that standard is not negligent. Contractor will use WCS Canadas Confidential Information only as is required by this Agreement, and will not reveal it to a third party without the prior written consent of WCS Canada, or unless it is required by law to reveal it. Confidential Information means information concerning each partys affairs, activities, research, proposals, projects, finances, property or method(s) of operation, trade secrets, know-how and similar information. Confidential Information does not include information which (a) is already known through lawful means to the receiving party before the other partys disclosure, (b) after disclosure, becomes generally known to the public through no breach or fault of the receiving party, (c) a party receives from a third party who is free to make such disclosure without breaching any legal obligation to the disclosing party under this Agreement, (d) the receiving party develops independently as evidenced by its own written records, or (e) is required to be disclosed by judicial or administrative process, in which case the party required to make that disclosure will notify the other of the obligation and cooperate reasonably with that partys effort to bar or seek a modification of the order. The term Contractor for purposes of this section shall include Contractor,

Job Description

Salary: $100,000-$20,000+ yearly salary + benefits (See below for more details)

About us:

Spring Financial is revolutionizing financial access for Canadians, providing smart credit-building, mortgage, and lending solutions. Millions struggle with high-interest debt and limited financial optionswere here to change that.
As one of Canadas fastest-growing fintech companies, annually we help 1 million customers explore their financing options with easeonline, via text, or over the phone. Our dynamic, innovative team thrives on collaboration, growth, and making a real impact.
To learn more about our products please visit our website here:

NOTE: This is a full-time, permanent, hybrid position in downtown Vancouver, with 3 set days in the office and 2 WFH.

Job Overview:

As a Machine Learning Engineer II, you independently design, build, and maintain machine learning systems that deliver impact for our customers and business. You are responsible for deploying reliable, scalable solutions from credit scoring models to intelligent automation and LLM-powered features. You work across the stack to connect ML systems with real user value.

You own end-to-end workflows: from data ingestion and transformation to model training, validation, and online inference. You actively contribute to model quality, observability, and performance optimization. You also help standardize development practices, CI/CD, and deployment tooling for ML systems.

You are expected to integrate modern AI techniques including LLM APIs, embeddings, and generative workflows where appropriate, and help evaluate how they can enhance products and operations. You use AI development tools to accelerate delivery and improve testing and debugging. You also build and maintain automated data pipelines and model services, working across real-time and batch systems.

You work closely with product managers, data scientists, and business stakeholders to clarify problems, evaluate feasibility, and align technical solutions with strategic outcomes. You are a key contributor to the evolution of Springs ML platform and culture.

What youll do:

• Own development of production-grade ML and AI systems from data to deployment.
• Build automated pipelines for training, feature engineering, and model serving.
• Use AI tools to improve development speed and integrate AI capabilities (e.g. LLMs) into products.
• Optimize systems for performance, latency, and cost.
• Collaborate with cross-functional stakeholders to scope projects and communicate results.
• Monitor, retrain, and improve models based on feedback and system metrics.
  
  

What You Should Already Have:

• Experience deploying machine learning models into production systems.
• Proficiency in Python and tools such as scikit-learn, TensorFlow, PyTorch, or HuggingFace.
• Strong understanding of model lifecycle, MLOps, and data pipeline design.
• Skills in inference optimization.
• Ability to collaborate with data, product, and business teams on impactful ML features.
• Experience with testing, monitoring, and CI/CD for ML systems.
• Know-hows on cost/benefit analysis for different ML solutions, e.g. Lambda vs. Sagemaker Inference, OpenAI vs. xAI API.
• Comfortable working with AI technologies (LLMs, embeddings, etc.) in applied settings.

What We Will Give You:

• Competitive annual salary ranging from 100,000 to 125,000+ , reflective of experience and impact.
• Comprehensive benefits package, including extended health, dental, and vision coverage with 100% of monthly premiums covered by the Spring.
• GRSP matching program to support your long-term financial goals.
• Transit-Friendly Employer (Transit allowance).
• A modern, collaborative workspace in the heart of downtown Vancouver.
• Ongoing career growth opportunities and the chance to help shape Spring Financials technology strategy and team culture.

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Please note : Upon applying, our Talent Acquisition team will review your resume. If you qualify, we will reach out to learn more about your experience and answer any questions you may have about the role, benefits, compensation, and more. Due to high application volume, we may not be able to respond to everyone.

Thank you for your interest! We appreciate your time and look forward to reviewing your application!

Job Description

Who We Are:

Muniworth is an innovative SaaS startup dedicated to municipal financial forecasting, empowering local governments to optimize budgeting and strategic financial planning. We are currently building an advanced Machine Learning and AI team to develop internal tooling, enhance our web applications, and create customized solutions for our municipal clients. If you're passionate about leveraging machine learning to drive impactful real-world solutions, Muniworth is the ideal place for you.

Who You Are:

You're an experienced Machine Learning Engineer excited by the prospect of working closely with a talented ML and AI team, under the guidance of our brilliant Lead ML Engineer. You thrive in environments with varied, challenging projects ranging from classic supervised and unsupervised ML tasks to advanced NLP, LLM, and RAG implementations. You're highly proficient with ML frameworks and libraries and ML Ops tools, and love finding innovative ways to apply ML and AI in solving complex problems.

What You'll Do:

• Design, build, and deploy robust machine learning pipelines and model serving infrastructure, ensuring reliable ML workflows from training to production.
• Write clean, maintainable code following software engineering best practices - while this isn't a senior engineering role, candidates should have demonstrated competency in creating readable, well-structured solutions that support collaborative development.
• Collaborate closely with our Lead ML Engineer and ML/AI team on projects spanning classical ML techniques, including feature engineering, dimensionality reduction, clustering, and classification, as well as NLP, Large Language Models, and RAG.
• Optimize model performance and scalability, leveraging your expertise in ML frameworks, model optimization, and distributed computing systems.
• Develop internal ML tools and customized AI-driven solutions for municipal clients, significantly influencing our product direction and company strategy through advanced analytics and predictive modelling.
• Own and manage specific ML-focused projects, balancing responsibilities between model maintenance, performance monitoring, and research into new ML approaches and techniques.

Requirements

What You Bring:

• 3+ years of industry experience in machine learning engineering.
• Proficiency using PyTorch/TensorFlow for implementing custom neural networks and training processes.
• Demonstrated experience writing clean, maintainable code with attention to software engineering best practices.
• Experience using transformer libraries (e.g. Hugging Face) for text classification.
• Experience utilizing traditional ML algorithms creatively to solve complex classification tasks.
• Experience using MLflow or similar for experiment tracking and model registry
• Familiarity using Docker for containerization and orchestration
• Familiarity using Apache airflow for pipeline automation
• Familiarity using Fast API/Flask for model serving APIs
• Familiarity with GitHub Actions for CI/CD
• Exposure to using Redis and Elasticsearch for caching and search
• A master’s degree in computer science, mathematics, statistics, or a related field—or significant practical experience demonstrating equivalent expertise beyond an undergraduate level.
• Excellent problem-solving abilities and strong communication skills, with the capability to articulate complex technical concepts clearly.
• Enthusiasm for innovation, adaptability, and actively contributing to team objectives beyond traditional role boundaries

Benefits

Why Join Muniworth:

• Competitive salary and comprehensive health and dental benefits.
• Flexible working hours (40 hours/week), tailored to your preferred schedule.
• Collaborative, intellectually stimulating environment emphasizing mathematics, innovation, and technical excellence.
• Modern, welcoming office located centrally in downtown Victoria, BC—100% in-person role.
• Regular team-building events and optional social activities.
• Directly influence critical municipal financial infrastructure, making a tangible impact on communities and local governments.
• For an ideal candidate with exceptional experience, we are open to offering compensation beyond the listed salary range.

Hiring Process:

We're actively hiring and eager to onboard exceptional talent as soon as possible. If you're excited by the intersection of data engineering and machine learning, thrive in a dynamic startup environment, and are motivated by meaningful work that impacts municipal governance, we'd love to connect with you. Please include a link to your public GitHub repository!

Job Description

Qorsa Corp is a Canadian technology company pioneering quantum-proof AI solutions for governments, enterprises, and institutions. We build and integrate advanced machine learning with cryptographically agile systems built for the post-quantum era to help our clients better understand and protect their data.

As a Machine Learning engineer, you’ll work on data ingestion and processing using various Natural Language Processing (NLP) tools. You will also work on building AI agents, fine-tuning LLMs, and building chatbots.

Key responsibilities include:

• Design, build, and maintain AI Agents using Langchain and other similar tools.

• Fine-tune and test LLMs on various verticals explored by Qorsa.

• Develop and deploy applications using Docker and Kubernetes.

• Improve on our existing technologies including data processing, natural language pipelines, and building knowledge graphs

Qorsa Corp is a Canadian technology company pioneering quantum-proof AI solutions for governments, enterprises, and institutions. We build and integrate advanced machine learning with cryptographically agile systems built for the post-quantum era to help our clients better understand and protect their data.

Qorsa Corp is a Canadian technology company pioneering quantum-proof AI solutions for governments, enterprises, and institutions. We build and integrate advanced machine learning with cryptographically agile systems built for the post-quantum era to help our clients better understand and protect their data.

Job Description

Our client is looking for a highly skilled Machine Learning Engineer to join their growing team in Mississauga. This role is ideal for a technically strong and experienced ML professional who thrives in a fast-paced, collaborative environment and is passionate about delivering scalable machine learning solutions on distributed systems such as Hadoop.

Key Responsibilities:

• Design, develop, and implement machine learning models using Spark ML for predictive analytics
• Build and optimize end-to-end training and inference pipelines on distributed platforms
• Process and analyze large datasets to uncover insights and engineer effective features
• Work closely with data engineers to integrate ML models into existing data pipelines
• Fine-tune models and hyperparameters to maximize performance and accuracy
• Develop scalable solutions for both real-time and batch inference
• Continuously monitor deployed models and address any performance issues
• Keep up-to-date with the latest tools, frameworks, and best practices in machine learning and distributed computing

• 10+ years of experience as a Machine Learning Engineer or similar role
• Expertise in Apache Spark and Spark MLlib
• Solid understanding of predictive modeling techniques (e.g., regression, classification, clustering)
• Hands-on experience with distributed systems such as Hadoop
• Proficiency in Python, Scala, or Java
• Strong grasp of data preprocessing and feature engineering methodologies
• Familiarity with model evaluation metrics and production deployment practices
• In-depth knowledge of distributed computing and parallel processing principles

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

The Software-Hardware System Optimization Lab continuously improves the power efficiency and performance of smartphone products through software-hardware systems optimization and architecture innovation. We keep tracking the trends of cutting-edge technologies, building the competitive strength of mobile AI, graphics, multimedia, and software architecture for mobile phone products.

About the job:

• Work on machine learning research, in particular for continual learning and their application in large language models (LLMs).

• Evaluate algorithms on general ML benchmarks or large foundation models such as LLMs.

• Keeping up-to-date on recent advances in related fields.

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long-term projects, the aim is to enhance state-of-the-art research while integrating innovations into the company's products and services, including LLMs, RL, NLP, computer vision, AI theory, and Autonomous driving.

About the job:

• Participate in the innovative LLMs reasoning and LLMs empowered AI agent research project;

• Implement algorithms for proposed models and applications, deploy into internal product;

• Work closely with researchers in the team;

• Keeping up-to-date on selected areas of ML and writing scientific reports;

• Provide insight report on the latest literature work.

Job Description

About ALTEN:
In just three decades, ALTEN has emerged as a global leader in Research and Development, Engineering, Information Technology Services, Life Sciences, and Network Services. Our footprint spans across 30 countries, with over 60,000 consultants driving innovation and technical excellence. Trusted by industry giants, we have become synonymous with pioneering solutions and unwavering expertise.

ALTEN CANADA , a proud subsidiary of ALTEN headquartered in France, is committed to serving the Canadian market. With local offices in Montreal and Toronto, we bring our global expertise to the forefront of Canadian innovation.

At ALTEN CANADA , our consultants thrive on tackling complex and highly technical projects across a diverse range of industries. From Manufacturing to Information Systems, IT Automation to Life Sciences, Energy to Automotive, Rail and Transportation to Telecommunications, Aerospace and Defense, our commitment to excellence knows no bounds.

Role : AI – Machine Learning Specialist
Locations:  North York, Toronto or Halifax, NS or Richmond, BC | Hybrid (3 days onsite from any of the locations)
Start Date:  ASAP
Contract Duration:  1 year (extendable) or option for Full time
Clearances Required:  CGP & Reliability

About the Role
Join a client, where AI is becoming central to mission. Client is leveraging satellite infrastructure to deliver real-time Earth observation services—from monitoring fragile ecosystems to tracking northern ice floes and shipping routes. Client’s team blends scientific and engineering expertise to develop cutting-edge algorithms that interpret diverse data types: images, sound, video, and text.

What You’ll Do

• Develop novel machine learning algorithms to interpret geospatial and multisource data
• Apply statistical analysis to validate model outputs
• Integrate complex algorithms into existing codebases
• Document technical performance and algorithmic design
• Mentor junior team members

• Machine Learning and/or Deep Learning
• Statistical and Probabilistic Analysis
• Python and C++ Development

• Experience with LLMs and Generative AI

• Collaborative mindset
• Strong communication and mentoring abilities

• Collective Insurance & RRSP
• Corporate Discounts
• 4 weeks of vacation
• Numerous corporate activities.
• Personalized professional development plans