Director, Machine Learning & Applied Science

Toronto, Ontario, Canada

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Software Development, Artificial IntelligenceIndustries

Requirements

Candidates must possess over 6 years of experience in applied machine learning, with a specialization in NLP, large language models, transformers, retrieval-based methods, and multi-agent systems. A minimum of 3 years of experience leading applied ML teams is required, along with strong Python programming skills and deep experience with frameworks like PyTorch and TensorFlow. Proven ability to collaborate with cross-functional teams and translate research into production-grade solutions is essential.

Responsibilities

The Director, Machine Learning & Applied Science will lead the design, development, and delivery of advanced NLP, LLM, and agent-based systems. This includes owning the scope, architecture, and delivery of ML models, actively reviewing research, adapting techniques into prototypes, and implementing/optimizing LLMs for reasoning and decision-making. The role also involves building and deploying intelligent agent workflows, leading and mentoring a team of ML engineers and applied scientists, driving project plans, and collaborating with Product, Design, and Engineering teams to integrate models and deliver customer value.

Skills

Machine Learning

NLP

LLM

Applied Science

Retrieval-Augmented Generation (RAG)

Multi-agent orchestration

System design

Prototyping

Model deployment

Intelligent agent workflows

Context-aware copilots

Tool orchestration

Continuous feedback loops

Technical leadership

Mentoring

Loopio

RFP response software for enterprises

About Loopio

Loopio specializes in simplifying the process of responding to Requests for Proposals (RFPs), Requests for Information (RFIs), Due Diligence Questionnaires (DDQs), and Security Questionnaires. Its main product is RFP response software that helps businesses manage and automate the intricate task of creating high-quality responses. The software features a smart content management system that organizes a company's knowledge base, making it easy for teams to collaborate, assign tasks, and review projects efficiently. Loopio operates on a subscription-based model, allowing clients to access its software and tools for a recurring fee. This model helps clients save time and improve the quality of their responses, enabling them to win more business. Loopio stands out from competitors by focusing on enhancing collaboration and efficiency for medium to large enterprises across various industries, including technology, healthcare, and finance.

Toronto, CanadaHeadquarters

2014Year Founded

$203MTotal Funding

GROWTH_EQUITY_VCCompany Stage

Data & Analytics, Consulting, Enterprise SoftwareIndustries

201-500Employees

Benefits

Remote Work Options

Hybrid Work Options

Phone/Internet Stipend

Professional Development Budget

Risks

Increased competition from established players like SAP threatens Loopio's market share.

Potential over-reliance on CRM integrations poses risks if policies change.

Recent layoffs may indicate internal financial or strategic challenges.

Differentiation

Loopio integrates seamlessly with CRM systems like Salesforce and HubSpot.

The Response Management Loop Framework offers a holistic approach to proposal management.

Loopio's smart content management system centralizes and organizes knowledge efficiently.

Upsides

Growing demand for AI-driven content management boosts Loopio's market potential.

Integration with CRM systems streamlines sales and proposal workflows.

Expansion into new markets enhances Loopio's global presence and capabilities.

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