Machine Learning Research Engineer

Numerator / Market Track, LLC; Toronto; On-site; CAD 80,000 - 120,000; Full time

Job summary

A leading market research company in Toronto is seeking a Machine Learning Research Engineer to develop deep learning models and systems for NLP tasks. The ideal candidate has over 2 years of experience building robust machine learning APIs and a background in deep learning. This role offers flexibility, wellness resources, and significant opportunities for professional development.

Benefits

Recharge Days

Maximum flexibility policy

Wellness resources for employees

Qualifications

• 2+ years experience building and deploying machine learning APIs in production environments.
• Experience building high throughput deep learning pipelines for NLP.
• Foundational understanding of deep learning modeling.

Responsibilities

• Develop and train deep learning models for NLP tasks.
• Build and maintain systems and data pipelines for delivering insights.
• Work closely with various teams to own project processes.

Skills

Machine Learning APIs

Deep Learning

NLP

Python

Pytorch

Education

Masters or PhD in Machine Learning or related field

Tools

Hugging Face Transformers

AWS

GCP

Job description

Machine Learning Research Engineer

Location: Toronto, ON, Canada
Req#: 604016

We’re reinventing the market research industry. Let’s reinvent it together.

At Numerator, we believe tomorrow’s success starts with today’s market intelligence. We empower the world’s leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it.

Numerator is looking for a passionate ML Research Engineer to join our growing Machine Learning team. This is a unique opportunity where you will get a chance to work with an established and rapidly evolving platform that handles millions of requests and massive amounts of events, and other data. In this position, you will be responsible for taking on new initiatives to design, build, deploy, and support high performance deep learning systems in a rapidly-scaling environment.

As a member of our team, you will make an immediate impact as you help build out and expand our technology platforms across several software products. This is a high growth and impact role that will give you tons of opportunity to drive decisions for projects from inception through production.

What You’ll Do:

• Develop and train deep learning models on computing clusters to perform NLP-related tasks, such as applying both pre-trained and custom transformers for NER, sequence classification, language modeling, etc.
• Develop LLM driven solutions using fine-tuning, RAG, and agentic patterns
• Build and maintain systems, APIs, and end-to-end data pipelines to deliver deep learning insights throughout all of Numerator’s products and platforms.
• Work closely with other Machine Learning Research Engineers, MLOps engineers, product managers, and other teams, both internal and external stakeholders, owning a large part of the process from problem understanding to shipping the solution.
• Have the freedom to suggest and drive organization-wide initiatives while being part of providing the technical

Skills & Requirements:

• 2+ years experience building and deploying robust machine learning APIs in production environments (ideally cloud-based environments such as AWS or GCP).
• Background in the foundations of deep learning modeling with experience building high throughput, production quality deep learning pipelines for NLP, computer vision, information extraction/retrieval, or related practice
• Production experience with LLMs including RAG, Evals, Agentic patterns, and information retrieval techniques.
• Foundational understanding of Python, Pytorch, and Hugging Face transformers library
• Knowledge in the latest NLP-related algorithms and methods such as LLMs, transformers, sequence-to-sequence models, word and sentence embeddings, attention, information retrieval, etc
• Experienced software engineering, data modeling, and debugging/profiling fundamentals
• A Masters or PhD in Machine learning, Computer Science, Mathematics, Statistics, or another quantitative discipline or 3+ years equivalent industry experience

Nice to Haves:

• Demonstrated ability to drive selection of machine learning approaches to solve specific problems coupled with the ability to clearly communicate tradeoffs
• Experience with one or more model inference optimization libraries (TensorRT, ONNX, torch script, vLLM, etc)
• General software design patterns (REST, MVC, Auto-scaling, etc.)
• Experience supporting machine learning solutions for multiple languages

Benefits:

Numerator is 2,000 employees strong. We have the confidence to be real and embrace what makes each Numerati unique. Our diverse experiences, ideas and backgrounds fuel our innovation.

Being part of the Numerati means that we’ll take care of you! From our Recharge Days, maximum flexibility policy, wellness resources for employees and their families, development opportunities and much more — we’re always finding ways to better support, celebrate and accelerate our team.